U.S. Bans New Foreign Mobile Robots

The U.S. Federal Communications Commission (FCC) “Covered List,” originally published in 2021, identifies communications equipment and services that it says pose a threat to national security. On 28 July, the FCC added mobile, communicating robots weighing more than 2 kilograms and power inverters commonly used in solar panels to the list, meaning that new products from any foreign country in these categories are no longer eligible for import. The move is a Department of Defense (DOD)-driven expansion of scattered federal efforts to further limit U.S. exposure to potentially sensitive Chinese technology, but it may impose major changes on the robotics industry in allied countries, too. The FCC’s announcement says that: All foreign-produced advanced robotic devices pose an unacceptable risk to the national security of the United States and to the safety and security of U.S. persons… unless the [Department of Defense determines that] a given foreign-produced advanced robotic device, or a class of such devices, does not pose such risks. There are two important definitions here. The first is what an “advanced robotic device” is, and the second is what “unacceptable risk” means. Drones already went through their own round of this sort of regulation, so they’re exempt from this particular restriction, as are connected vehicles and medical devices. As far as the FCC is concerned, “advanced robotic devices” are mobile systems that incorporate on-board sensing and communications and have some amount of autonomy. There are a couple of loopholes, including systems weighing under 2 kg and any system that communicates at less than 200 kilobits per second, which opens up some creative possibilities. It’s important to note that this applies to new devices; those already certified are not restricted for sale or use. As to the risks, the U.S. government says that foreign advanced robotic devices represent: “a cybersecurity risk that threatens the security of critical infrastructure and thus the safety and security of U.S. persons.” There seem to be two main points to the justification, found in Appendix C . The first is that mobile robots are important to both the economy and the military, so the United States needs its own supply chain and industrial base rather than relying on foreign manufacturers. And second, mobile robots monitor critical infrastructure in sensitive locations, making them a security risk. The Country That Must Not Be Named As part of its justification for why foreign robots are a security risk, DOD cites IEEE Spectrum’s article on a critical vulnerability in robots from Unitree , based in Hangzhou, China, along with several other news articles and reports about Chinese robotics. And despite the FCC swearing up and down that this action is “country neutral” and “not targeted at any country or countries,” U.S. national security sources told Spectrum that the perceived threat is obviously China. That’s how China feels about it, too, per a Chinese Ministry of Commerce 29 July press conference (translation of the first quote here ): On the surface, the FCC’s measures fly the banner of “non-discrimination,” but in substance they discriminate against and suppress Chinese enterprises and products… China firmly opposes the U.S. overstretching the concept of national security and going after Chinese companies. Protectionism does not make the U.S. more competitive and will only hurt the interests of U.S. companies and consumers. China will continue to do what is necessary to firmly defend the legitimate and lawful rights and interests of Chinese companies. It’s unclear what China is going to do about this—but how about the rest of the world? How can foreign companies that make advanced robotic devices get them cleared for FCC authorization? Among many, many other things , you’ll need to provide “a detailed, time-bound plan to establish or expand manufacturing in the United States for the advanced robotic device.” Because China also produces a large fraction of robot components, even for robots assembled in the United States, it will have strong leverage in any related negotiations until U.S. robotics companies further diversify their supply chains. RELATED: Proposed Chinese Robot Ban Is Latest U.S. Tech Sovereignty Move Applicants must also submit their applications to the DOD and FCC by 1 January 2028, which is unfortunate for anyone who wants to develop an advanced robotic device after that point. Robotics Industry Reactions This is all very new, and reactions from the robotics community have been mixed. Some American robotics companies may benefit in the local market from the newfound lack of competition in the commercial market. Brendan Schulman, Boston Dynamics ’ vice president of policy, wrote an enthusiastic endorsement of the ban on LinkedIn : “I sense that this is just the first round in a series of policies that will define the success and growth of the industry for decades to come.” On the other hand, third-country buyers may just stick to Chinese products , as they generally have for drones and electric cars. But not all companies expect major changes from the new regulation. American customers “need to know they can audit the technology, get support quickly, and keep the system operating without depending on a fragile overseas supply chain,” Nic Radford , the CEO of U.S. humanoid robotics company Persona , tells IEEE Spectrum . In other words, he figures some customers wouldn’t have wanted Chinese humanoids anyway. Philipp Frey , vice president of strategy for Swiss quadruped company ANYbotics , agrees. He says their enterprise customers in the United States “increasingly evaluate robots on long-term reliability, cybersecurity, software capability, safety certification, serviceability, and ecosystem integration, not on hardware cost alone.” ANYbotics also plans to apply for conditional approval of future products, Frey says. That will involve a national-security review by DOD or the Department of Homeland Security, disclosing company beneficial ownership, supply chain risks, and declaring a plan for establishing a significant manufacturing presence in the United States. U.S. quadruped company Ghost Robotic ’s CEO Gaven Kenneally is more explicit about the risks Chinese robot strategy poses to the United States. “Active and purposeful spyware is deployed inside the U.S. on Chinese robots. Examples of predatory pricing abound. And this isn’t just a competition between U.S. and Chinese robotics companies; it’s between private U.S. companies and China’s coordinated national strategy,” Kenneally tells Spectrum . “If today’s announcement encourages stronger cybersecurity and a more level competitive environment, that’s good for customers and good for the robotics industry.” So is an industry-wide ban the best way to guard against threats? American approaches to Chinese technology security risks have been “ad hoc and fragmented,” wrote Brookings Institution sociologist Kyle Chan in a report published 9 July. Chan called for the Bureau of Industry and Security, part of the Department of Commerce, to centralize federal information gathering and decision-making on how to handle risky foreign devices. He also called for better public input mechanisms for these issues, and a continuous, proportionate process that tightened or relaxed targeted import restrictions in response to well-defined risks. That would allow American industry to continue benefiting from partnerships with Chinese manufacturers in less sensitive links of the supply chain, Chan argues. Those links will evolve over time, requiring continued assessment, but without those partnerships, crude bans “could make it more difficult for American startups and researchers to develop new software and end up slowing innovation across the U.S. robotics ecosystem,” he writes.

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Walden Robotics Partners With Toyota on Practical Humanoids

For a while there, it seemed as though robotics as a whole was stuck in a mad rush towards building humanoid robots mostly because it was very possible (and very lucrative) to do so, even without a near-term end goal that was necessarily realistic. Some of the magic of those first couple of years of the humanoid explosion has stuck around, but there’s also been an industry-wide sobering leading to pointed questions about practicality and value . In other words, starting a commercial humanoid company now is a much different proposition than it would have been just a few years ago. On 15 July, Walden Robotics emerged from stealth with US $300 million in funding at a valuation of $1.1 billion. Walden is a spinout of Toyota Research Institute (TRI), and it’s spent the last 10 or so years working on hard problems in robotics with the goal of transitioning from research to real-world applications. That seems like the amount of time and experience that it might reasonably take to develop a practical and value-driven approach to deploying general-purpose humanoid robots, and Walden has chosen an excellent starting point by skipping the legs. “It’s ironic,” says Walden co-founder and CEO Russ Tedrake . “I thought about legs for 20 years; that’s the class I teach at MIT. There are many reasons to build a robot with legs. But the question is, what’s the addressable market? And what percentage of it is covered by a wheeled base?” It’s this focused, practical thinking that sets Walden somewhat apart from many (if not most) of the other companies in this space. Rather than developing a robot first and searching for a viable commercial use case second , Walden instead identified applications where robots can provide value now, and designed a robot that could safely and efficiently meet those needs. Walden Robotics Walden Robotics’ Manufacturing Focus Russ Tedrake is the CEO and co-founder of Walden Robotics. Walden Robotics Tedrake is light on the details about what specific applications Walden is targeting at this point (citing confidentiality with current commercial partners). Manufacturing and logistics environments where there are a lot of relatively simple and repetitive tasks that aren’t friendly to conveyor belts and pre-programmed robot arms are a good bet. Even in these environments, however, robots still have to find a useful niche, because they’re going up against human workers who are more flexible while also cheaper to employ. So the question is: how do you make an argument to a customer that a robot is actually a better solution than their existing human workers? “You need to find applications with high utilization—where the robot is used 24 hours a day, 7 days a week,” says Tedrake. “Manufacturing is a global imperative right now, and it makes the economics work.” Economic viability is a necessary condition, but it’s not a sufficient one for Walden, or for their partnership with Toyota. People are a big part of Walden’s plan, too. One of Walden’s major strengths is the company’s partnership with Toyota, which is not all that surprising given that Walden is a spinout from TRI, which is Toyota’s Silicon Valley-based R&D arm . “Toyota was very proud of the work we had done at TRI, and was ready to go big in this space,” says Tedrake. “Part of the excitement of having Toyota as a partner is that their culture is deeply people-first. When talking to Toyota’s leadership, I was never asked how much money this is going to make, but I was asked how it will improve the quality of life for all people.” The robot’s chonky design allows it to meet the high payload requirements of useful manufacturing work. Walden Robotics In this context, at least in the short term, Walden’s approach to improving the quality of life for people is to take over those aforementioned repetitive manufacturing tasks with robots. Tedrake hopes that this will lead to workplaces where skilled craftspeople are able to do even more with their hard-earned expertise, increasing their efficiency, productivity, and happiness all at the same time—a noble goal, although there’s only so much Walden itself can do to make this happen, and not all customers will share Toyota’s priorities. Wheeled Humanoid Robots in Factories Many other humanoid robotics companies are also targeting these logistics and manufacturing spaces with general-purpose robots, and they’re doing so by making robots that are as human-like as possible. The theory is that a humanoid form factor is necessary when operating in human environments. And there are certainly arguments in favor of a humanoid with legs—stairs exist, for one, and legged robots have a smaller footprint compared to wheels. But a large wheeled base offers some significant advantages, as Tedrake points out. You’re incentivized to cram the base full of batteries, since more weight near the floor keeps the robot stable, which also solves the problem of running out of power during the middle of the workday. More importantly, a statically stable robot that moves around on a wheeled base can bypass the safety challenges that are currently keeping legged humanoids physically separated from real humans—most prominently, the fact that legged robots can fall over. “Factories already have autonomous mobile [wheeled] robots,” explains Tedrake. “They already have safety cases built around AMRs. You can piggyback on that with a wheeled base.” Simple, rugged grippers make the robot suitable for commercial deployment. Walden Robotics Walden’s perspective on manipulation is similar. Many humanoid companies are using five-fingered hands that are highly dexterous, but also highly complex, which Tedrake believes is not a pragmatic approach in the context of commercial deployments. “There’s a question of what you need to do the tasks, but the real question is just durability,” Tedrake says. “We have been deployed in a Toyota factory, and at the end of the week, the hands take a beating, so we built hands that can take that. I have not seen a more dexterous hand that could have done the work our hand has done.” Walden’s long-term plan is to build “general purpose robots.” It’s not always clear what a general purpose robot is, because (I would argue) nobody is quite sure what “general purpose” means. It’s certainly not referring to robots that can do everything ; I think the closest we can get are robots that can be taught to do a useful number of different skills, which is why I prefer the term “multi-purpose.” It’s a little pedantic, I know, but I think the distinction is important because it moderates expectations in the near term. Part of where Walden’s optimism towards general purposeness comes from is TRI’s earlier research on diffusion policy , which helps robots learn new skills more quickly by leveraging previously learned skills as a foundation. “Fundamentally, multi-tasking is a way to get to a general purpose robot,” Tedrake says. “I believe there is a single platform that can do a lot of tasks that are of high value for real customers. That will give us the experience we need to give birth to this deployed general-purpose capability.”

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Video Friday: Meet Google DeepMind’s Gemini Robotics 2

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. Actuate 2026 : 18–19 August 2026, SAN FRANCISCO IROS 2026 : 27 September–1 October 2026, PITTSBURGH Humanoids Summit Seoul : 22–23 September 2026, SEOUL Enjoy today’s videos! Introducing Gemini Robotics 2—the intelligence layer powering the next generation of truly adaptable robots. As it takes its first literal steps, this major advance unlocks intelligent whole-body control, advanced dexterity, and multi-robot collaboration. [ Google DeepMind ] THE ROADMAP! NOOOOO! [ Agility ] Videos like this always make me wonder how repairable these robots are. Very, I would hope. [ Unitree ] Humans routinely communicate through abstractions of their bodies, including shadows, silhouettes, and reflections. Here, we present a robotic system capable of dynamic shadow expression using a 21-degree-of-freedom dexterous hand with compliant soft skin and a learned shadow self-model. [ General Robotics Lab ] Human to quadruped motion transfer is an odd concept but I’m here for it. [ Disney Research ] Meet Stretch 4.0 —The one-armed, three-wheeled robot that can navigate your home safely. Would you rather a humanoid robot or Stretch? [ Hello Robot ] And now, this, for some reason. [ PNDbotics ] I’m not sure we’re allowed to be impressed if you resize a badminton court to accommodate your robot. [ PHYBOT ] Golden eagles care not for drones . [ Team BlackSheep ] USC researchers work with NASA and others to train robot dogs for planetary exploration on Mars, the moon and beyond! [ Research in Applied Decisions: RAD Lab ] Thanks, Cristina! WABOT-1 was arguably the birth of the humanoid robot in Japan. We’ve come a long way, and it’s good to be reminded where we started. [ Takanishi Lab ] If only this video was at 1x instead of 5x we could have had 15 hours of Memo folding laundry. [ Sunday Robotics ]

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Video Friday: An Italian Humanoid Comes to Life

Your weekly selection of awesome robot videos Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO IROS 2026 : 27 September–1 October 2026, PITTSBURGH Humanoids Summit Seoul : 22–23 September 2026, SEOUL Enjoy today’s videos! In just six months, our team turned GENE.01 into a fully functional humanoid platform that can walk, sense and interact. Its full-body multimodal skin perceives touch, proximity, force and temperature, bringing Physical AI closer to safe and natural collaboration with people. Not a render. Not a concept. This is GENE.01. The future of Physical AI is taking its first steps. [ Generative Bionics ] Why create robot intelligence for just one hand, when we could have it learn from many? GEN-1, our latest embodied foundation model, now supports a broad range of end effectors from 5-finger hands, to specialized tools, and everything in between. Each hand is a different sensorimotor interface by which GEN-1 experiences the physical world. Scaling pretraining across thousands of these interfaces teaches GEN-1 a universal physical commonsense that transfers to new hands and new ways to grasp, push, pull, twist, and more. And to illustrate this concept, a surprise spatula. [ Generalist ] This paper presents the design, fabrication, and flight validation of a flat-packable flying wing built primarily from corrugated cardboard. The aircraft is manufactured from three laser-cut sheets and assembled through a fold-and lock architecture that forms load-bearing wing structures with minimal tooling and no permanent fasteners. The full airframe can be assembled in under 15 minutes, demonstrating strong potential for rapid deployment, low-cost logistics, and scalable field use. [ AIR Lab ] A $14k open-source data-collection system that includes beat-down capability. [ MEVION ] Thanks, Kento! Together with Niantic Spatial and NVIDIA, [we] can now scan a real deployment site with off-the-shelf hardware, reconstruct it into a photorealistic Gaussian splat, and run massively parallel RL [reinforcement learning ] training. The policies trained in our Gym environment then transfer zero-shot to the real robot and environments they were trained for. This enables faster deployment of more capable and robust policies for the end user. [ Flexion ] I don’t know why, but the version of TRON 2 with the stubby little legs is just adorable. [ LimX Dynamics ] Uh, get a real job already...? [ PNDbotics ] Well I guess we can all stop asking what humanoid robots are good for. [ EngineAI ] I think the right thing to do here is only post the disclaimer included with this video: “This film is a conceptual creative production, and certain scenes are presented for demonstration purposes only and do not represent the actual in-store operating process. The final store environment, robot appearance, and functionality are subject to the actual deployment. During actual operations, the robot will autonomously perform only designated preparation steps for specified ice cream products, and its hands will be fitted with protective gloves that comply with applicable food safety requirements.” [ Sharpa ] Drone delivery is now an essential part of the South West London Pathology (SWLP) modernization agenda. Since February 2026, our highly automated aircraft have been delivering urgent NHS samples across south west London, with service up to 85% faster than ground transport. We are thrilled to be part of this initiative, supporting clinicians in providing timely, effective care for patients and contributing to a greener, more resilient NHS. [ Wing ] Take a closer look at what’s next for the Aurora Driver. Designed to move freight farther, faster, and more efficiently, this next generation of the Aurora Driver delivers greater performance, built to last one million miles, and cuts hardware cost in half. [ Aurora ] How does a robot learn to recognize an object it’s never encountered? In this case, a demo can be worth a thousand words. Short human demonstrations can be used to create fully automated training datasets, sidestepping the prompting limitations that hold back vision-language models. Rather than describing objects with language, the system tracks what a person touches and manipulates during a demo, follows those objects through time, and clusters detections to handle objects merging or splitting apart in the scene. This bypasses a core weakness of VLMs, which struggle to reliably detect unusual or novel objects even with repeated, carefully engineered prompts. [ Robotics and AI Institute ]

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Video Friday: Your Robot Surgeon Will See You Now

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO IROS 2026 : 27 September–1 October 2026, PITTSBURGH Humanoids Summit Seoul : 22–23 September 2026, SEOUL Enjoy today’s videos! In this work, we present a systematic evaluation of contemporary humanoid technology for laparoscopic surgical tasks. We develop a humanoid-based laparoscopic teleoperation framework using general-purpose instruments and assess its capabilities through benchtop characterization, dry-lab user studies spanning diverse surgical experience levels, and in-vivo porcine studies. Across these evaluations, we quantify technical feasibility, task performance, and clinical readiness relative to established surgical platforms. Together, our study provides an evidence-based assessment of the current capabilities and limitations of humanoids for surgical applications, highlighting both their promise and the key technical challenges that must be addressed before clinical deployment. [ UC San Diego ] Thanks, Ioana! Today, we preview ACT-2, the first robotics model to achieve reliability by unifying broad generalization with high performance. Sunday also has this three hour video (!) of Memo folding laundry in “never seen environments.” Let’s just not ask, because we almost certainly don’t want to know. [ Sunday Robotics ] Spot is not the first quadruped to try its legs at last few meters package delivery , but the challenge is not really those last few meters—it’s going to be not driving the human co-worker nuts, is my guess. [ Boston Dynamics ] Quadrupedal locomotion in complex environments requires multiple motor skills, stable gait transitions, and perceptive control over a broad range of speeds. APT-RL (Action Pretrained Transformer-based Reinforcement Learning) is a unified framework for high-speed, multi-skill locomotion. A single policy selects and transitions between gaits and motor skills using only onboard perception and computation. In real-world experiments, KAIST HOUND traversed stairs, hurdles, stepping stones, gaps, and fallen branches. It reached an instantaneous peak speed of 4.25 m/s while traversing a 60-cm step and 6 m/s during a drop-down transition on a three-step staircase. [ KAIST DRCD Lab ] We will have much more on this next week. [ Walden Robotics ] Today, we introduce Lumo-2, our next-generation latent world-action model for generalist embodied robot learning. [ Astribot ] Following Atlas’ first-of-its-kind live performance at the FIFA World Cup 2026™, we caught up with Seth Davis, senior program manager, to learn how this demonstration came together and what it takes to succeed in the field (and on the pitch ). [ Boston Dynamics ] No teleoperation. No cuts. Long take. One of the world’s few complete demonstrations of long-horizon mobile manipulation, bringing fully autonomous humanoid robots another step closer to us. [ LimX ] Thanks, Jinyan! Impressive. But get a job. [ MagicLab ] We saw some footage of this last week , but here’s a much better video. Wing-propelled diving birds flap their wings to move through air and water, yet the wing morphology and kinematics that enable this behavior remain poorly understood because of the difficulty of collecting in situ data. The impact of flapping frequency, wing size, and stiffness on locomotion in—and transition between—the two media are still unknown. We compared data from diving birds against experiments using a flapping-wing robot capable of flying, swimming, plunge diving, and exiting the water. We show that frequency adaptation, flexible wings, and powerful actuation enable seamless transitions without folding wings or legs, that large wings enhance flight without substantially reducing underwater efficiency, and that tail-body distance and egress angle affect water exit. These results clarify how birds (and robots) balance multifluid locomotion constraints. [ EPFL LIS ]

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How to Make an Invisible Drone

There are many words that I would never, ever use to describe a drone. Stealthy. Subtle. Whatever the opposite of obnoxious is. Much of this is because of the giant angry bee sound that drones tend to make, but it’s also the way that they look in flight: With uncannily linear movements and an even less canny ability to hover perfectly still, they tend to draw the eye as affronts to nature. In a paper presented this week at RSS 2026 in Sydney, roboticists from Northwestern University, Evanston, Ill. demonstrated a drone called Phantom Twist that is essentially invisible to humans, being an order of magnitude more difficult to see in flight than a typical quadrotor. They accomplished this with the aid of computational design, and while the resulting hardware is, I would argue, also an order of magnitude more of an affront to nature than a typical quadrotor represents, it’s pretty amazing how well it works. Phantom Twist spins so fast, it’s practically invisible. Michael Rubenstein/Northwestern University The trick here is easy to see, even if the drone isn’t. By spinning in flight at between 15 and 25 Hz, Phantom Twist takes advantage of humans’ decidedly mediocre visual system to turn a solid spinning object into an opaque smear. Human eyes take some amount of time (typically about 100ms) to integrate what we see before sending the full scene off to our brains for processing. Moving objects can cause problems for this system, because if the movement is fast enough, our eyes are forced to average that motion across the scene, combining it with whatever is in the background and resulting in a transparent blur. This effect is called ‘persistence of vision.’ For something that spins like Phantom Twist, that motion blur comes from the drone’s rapid rotation and it works because most of the drone is cleverly designed to be empty space. Drones that spin in flight are nothing new—we’ve covered a bunch of them in the past, including Picolissimo and any number of samsara drones inspired by the spinning flight of maple seeds. What makes Phantom Twist unique, and also very odd, is that the design was computationally optimized for low visibility. Controlling how drones like this fly Before we get into that, though, a quick note about how drones like this can even fly controllably, because it’s not at all obvious. With just a single motor and no control surfaces, the only possible control input is through the motor itself, and by pulsing the motor speed up or down at just the right time during each rotation, the drone can translate in any direction. Altitude control comes from changing overall motor thrust, and its spinning nature makes the drone passively stable. Carbon fiber rods connect batteries, a controller, some counterweights, and a motor and propeller. The research robot also includes optical tracking tags. Michael Rubenstein/Northwestern University The bits that you need for this kind of drone include the motor and propeller, a couple of batteries, a controller, some counterweights (which could be replaced with more batteries or payload), 0.8mm carbon fiber rods to tie it all together, and a connector for the handheld launcher that gets the whole thing up to speed. The actual arrangement of these components is surprisingly flexible, and that’s where the invisibility comes in. “The design space is high dimensional,” explains Northwestern’s Michael Rubenstein . “It’s very difficult for a human to reason through all the tradeoffs between the physical constraints required for stable flight and the visual appearance of the spinning drone, and I don’t think we would have easily arrived at this low visibility design ourselves.” The visibility (or not) of Phantom Twist is primarily driven by the extent to which different components line up with each other from the perspective of someone looking at the drone. The more components that line up with each other as the drone flies, the less background you see through the spinning drone, and the more visible the drone becomes. Because you might be looking at the drone from a number of different angles, and also because the drone has to be stable enough for controlled flight, there are a bunch of different things that need to be optimized all at once, which is why computational design is effective here. Phantom Twist’s final design was generated using an iterative optimizer which had a goal of minimizing a metric called “Learned Perceptual Image Patch Similarity ,” or LPIPS, while making sure that the design could still physically work. LPIPS is the difference between two images: a background image, and a background image with an overlay of the simulated spinning drone. The smaller that difference is, the more invisible that design is. It’s tricky for a human to consider all of the variables at once, but Rubenstein says that the final design does make intuitive sense, because “the automated pipeline prefers placements where components don’t visually overlap as it spins, or where the components are too close to the center of rotation.” Two iterations of Phantom Twist drones are shown with their handheld launching mechanisms. The better optimized version (bottom row) relocates the launcher interface to remove components that are too close to the central axis, making them more visible. Michael Rubenstein/Northwestern University Out of a starting set of around 20,000 feasible Phantom Twist configurations, the optimized design (the one that you see or don’t see in the pictures and videos) has a LPIPS score of 0.0104. A human-designed Phantom Twist is about twice as visible, with a LPIPS score of around 0.2, and a conventional quadrotor (of the same size) would be over ten times more visible. And there’s still a bit more optimization that could be done with the electrical wiring as well as increasing the baseline transparency of the components themselves. Phantom Twist is currently controlled using an optical tracking system, which means that it’s not yet capable of flying outside of a controlled environment. But Rubenstein has built other drones along similar principles in the past, which have successfully flown outside, and he’s optimistic about using those techniques to break Phantom Twist out of the lab. The spinning behavior might even enable some useful sensing capabilities, he says. “An interesting possibility is mounting a camera on the spinning body. As the vehicle rotates, it could capture imagery in every direction, effectively creating a 360 degree view of its surroundings that could be used for onboard navigation and control.” As for what a drone like Phantom Twist could be used for—assuming that the sound can be mitigated somewhat (and there are potential approaches to making that happen ), a stealthy microdrone could do all sorts of things with covert surveillance being the most obvious application. For his part, Rubenstein says that he’s personally excited about the potential for watching wildlife, “where a less intrusive drone could observe animals while minimizing its impact on their natural behavior.” The elephants in particular would certainly appreciate that . For a deeper dive into all the particulars of this project, read the paper: Computational Design of a Low-Visibility UAV Using a Human-Aligned Perceptual Metric , by Jingxian Wang, Chen Yu, David Matthews, Emma Alexander, Sam Kriegman, and Michael Rubenstein from Northwestern University, which is being presented this week at RSS 2026 in Sydney .

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Video Friday: A World Cup for Robots

Video Friday is your weekly selection of awesome robotics videos , collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO IROS 2026 : 27 September–1 October 2026, PITTSBURGH Humanoids Summit Seoul : 22–23 September 2026, SEOUL Enjoy today’s videos! For the first time, two full teams of humanoid robots played an 11-vs-11 soccer match on hardware, bringing one of robotics’ most ambitious long-term visions closer to reality. Never before have two full-sized humanoid robot teams played a soccer game against each other. [ RoboCup ] Engineers at MIT and EPFL in Lausanne, Switzerland, have designed a robot that can swim underwater, and flap out of the water to continue flying through air, much like a diving bird. The robot can help scientists study the mechanics that enable these actions in aquatic aviators and may help launch a new class of aerial-aquatic drones and vehicles. [ MIT ] We’re excited to announce our breakthrough robotic hands for the NEO platform: hands that match or exceed human-level dexterity, strength, safety, and reliability. Designed from the ground up, these 25-DoF hands combine 25 fully actuated degrees of freedom with a tendon-driven system, rich tactile sensing, and built-in compliance. The result is a hand capable of true in-hand manipulation, precision tool use, and delicate interaction. [ 1X ] This match, Tech United played against IRIS at the mid size league at RoboCup 2026 in Incheon South-Korea. [ Tech United ] Atlas arrived pitchside at NYNJ Stadium in front of 80,000 people gathered to see Brazil vs Norway. After performing some of the sport’s most memorable player celebrations, Atlas helped kick-off the second half by delivering the match ball! [ Boston Dynamics ] Navigating discrete terrain such as stepping stones remains a major challenge for legged robots. Conventional approaches often rely on dense environment reconstruction from cameras or LiDAR, which can be affected by latency, occlusions, and significant computational overhead. We show that proximity sensors integrated into the bottom of a quadruped’s feet enable safe, terrain-seeking autonomous locomotion. [ Paper ] On this holiday, Digit is on grill duty. It turns out precise force control is good for more than payload handling. Happy 4th of July from all of us at Agility. [ Agility ] We’ve created GEN-1, our latest milestone in scaling robot learning. We believe it to be the first general-purpose AI model that crosses a new performance threshold: mastery of simple physical tasks. It improves average success rates to 99% on tasks where previous models achieve 64%, completes tasks roughly 3x faster than state of the art, and requires only 1 hour of robot data for each of these results. GEN-1 unlocks commercial viability across a broad range of applications—and while it cannot solve all tasks today, it is a significant step towards our mission of creating generalist intelligence for the physical world. [ Generalist ] 4 years at Figure. [ Figure ] Reachy Mini is becoming your real AI companion. The Conversation App makes it able to talk fluently with you, help you with your to-do list, remind you of important tasks, and even chat about music. Long-term memory, voice interaction, always ready to help. [ Reachy Mini ] Is this sort of thing now a real job for humanoid robots, then? [ Unitree ] Quite a story, but is it a real job? [ EngineAI ] If you have a cute animal logo for your research I will always share it. [ BIEVR-LIO ] This is very delicate work, although the real challenge would be picking those nuts out of a jumbled bin full of randomly sized nuts, which is how most of us live our lives. [ Sanctuary ] Not for me, thank you, although I’m not saying that most of the other humanoid robots out there are any better looking, fundamentally. [ UBTECH ] Robotics professor, Dr. Christian Hubicki, judges robot soccer skills while knowing very little about soccer himself. [ ORL ] In this presentation, Brendan Schulman, Vice President of Policy at Boston Dynamics, outlines the critical role of government engagement in driving the success of the humanoid robotics industry. He demonstrates how legged robots like the Spot quadruped and Atlas humanoid are moving beyond factory settings to deliver real-world value in infrastructure inspection, industrial manufacturing, and public safety. Schulman highlights the intersection of AI and robotics, showcasing how large behavioral models and reinforcement learning enable robots to navigate slippery floors and autonomously avoid workplace hazards. Ultimately, he calls for a proactive national robotics strategy focused on workforce training, safety standards, and ethical frameworks to support supply chain resilience and global competitiveness. [ Humanoids Summit ]

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Video Friday: An Earthbound Mars Rover for the Moon

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO IROS 2026 : 27 September–1 October 2026, PITTSBURGH Enjoy today’s videos! NASA is considering a mission concept for an advanced, nuclear-powered rover to be deployed to the Moon’s South Pole as part of the agency’s Moon Base plans. The PROMISE (Polar Rover for Observation, Mapping, and In-Situ Exploration) mission concept relies on the Curiosity Mars rover mission’s testbed rover. Some elements of the Perseverance Mars testbed rover shown in this video could be used as well. As exact duplicates of Curiosity and Perseverance, the testbed rovers are equipped with flight-proven engineering systems capable of carrying technology as well as science instruments that would advance Moon Base efforts. A Mars rover for the Moon? That’s some OPTIMISM right there. [ JPL ] This is the absolute best thing since Festo’s AirPenguin . The project explores soft, lightweight robots that can gently float around people in indoor environments and invite playful, affectionate, and everyday interactions. Unlike conventional drones, our robot is designed to be quiet, soft, touch-safe, and socially approachable. Through this work, we ask what future indoor companion robots might feel like if they were not rigid machines, but gentle floating beings that share space with us. [ Paper ] Thanks, Mingyang! Today, we’re launching our home robot, Isaac 1. Deliveries will begin this fall. US $500 per month, with some basic task autonomy plus teleoperation. [ Weave Robotics ] A couple things from this new Figure video—thing one is that the cart pulling is a good illustration of how clumsy humanoid robots still are at basic tasks relative to humans. Thing two is that there are absolutey no humans anywhere near these robots. You can see one guy at 0:19, which I can only assume is an accident, because these robots are not safe to be around from an industrial safety perspective. [ Figure ] Our very own Kohava Mendelsohn met some robots at ICRA in Vienna, and only one of them was murderous. [ ICRA 2026 ] Welcome to Robot Park, where we’re building the future with Apollo 2. Robot Park is where Apollo learns today, getting the experience needed to make a difference tomorrow. Today we’re announcing Robot Park, our nearly 90,000-square-foot facility where Apollo 2 is collecting real-world training data needed to advance autonomous humanoid robots. [ Apptronik ] UBTech Robotics, the world’s first publicly traded humanoid robot-maker, has launched a humanlike robot that features lifelike silicone skin and “emotional AI”, as Chinese tech firms increasingly transition robots from the factory floor to the family living room. [ SCMP ] Spherephones are redefining how we experience sound. Created at Georgia Tech, this wearable uses spatial audio to alert users to movement from every direction—including behind and below. Built for safer human-robot collaboration, the technology is expanding into gaming and accessibility applications. See how music is becoming a new language for awareness and interaction. [ Georgia Tech ] Humanoid robots are meant to carry out long-horizon autonomous missions in a world built for humans. This is hard. These missions consist of many steps, each of which requires them to perceive, navigate, and interact with the environment. This is exactly Flexion’s goal: building the general-purpose intelligence that turns any robot into a useful helper. [ Flexion ] We’re introducing KinetIQ Ascend — our reinforcement learning approach designed to reach 99.9% manipulation reliability at human speed and beyond. [ Humanoid ] Dr. Sebastian “Basti” Scherer has worked in field robotics since the first DARPA Grand Challenge in 2004. He runs the AirLab at Carnegie Mellon’s Robotics Institute and is the Director of Safe Embodied AI at FieldAI. While much of the industry is focused on local skills like tabletop manipulation, Dr. Scherer sees the greatest value in solving dirty, dull, and dangerous tasks that require operating in uncertain environments where the robot needs to “just work.” When robots “just work” they become less like robots and more like tools. “That’s the big challenge that we have to overcome,” he says, “and that’s the challenge that FieldAI is really primed to solve.” [ Field AI ] Look, I really appreciate how valuable robots like ElliQ can be, and robots that do good work and offer a financial benefit are incredibly important, especially in the context of family care. But in my opinion, you really shouldn’t suggest that a robot with FaceTime or whatever is an equal replacement for in-person human companionship, nor should you suggest that AI can replace a human wellness coach. If you can’t afford those things, then sure, ElliQ can offer some of those capabilities in a very limited way, but that’s all. [ ElliQ ] Very cool moves! Now get a job! [ DEEP Robotics ] Drawing inspiration from restaurant waiters in Morocco and Turkey, among other places, we equip a robot with a hanging tray to transport objects from one location to another without dropping them or spilling their contents. We incorporate this approach into an interactive robot waiter demonstration, which uses computer vision and visual servoing to steer toward a person with a raised hand to serve them. [ Paper ] If you’re going to make robots wear skirts or shorts or pants, you have to give them butts, or it’s just not going to work. That is all. [ TechShare ] via [ Kazumichi Moriyama ] It’s Los Alamos, so of course we have robots. Some work inside gloveboxes, while others probe unexploded ordnance in the field and aid with repetitive lifting, Doc Ock–style. Legend has it there’s a fro-yo robot in the cafeteria. [ LANL ] Here are a couple of talks from the recent Humanoids Summit in Japan, from Ali Agha of Field AI as well as Hiroshi Ishiguro. [ Humanoids Summit ]

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Video Friday: Give Robots a Hand

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO IROS 2026 : 27 September–1 October 2026, PITTSBURGH Enjoy today’s videos! The best way of introducing a new robot hand is to have a disembodied one crawling across a table. [ Tangent Robotics ] MIT CSAIL’s Improbable AI Lab Director Pulkit Agrawal explains his “SoftMimic” approach to making robots safer around humans. [ SoftMimic ] I now have absolutely no interest in a humanoid robot for my home unless it can do this. [ PNDbotics ] The DARPA Lift Challenge is open to the public Aug. 6-9, 2026, at the National Museum of the US Air Force. [ DARPA ] Getting Digit to step and shuffle around an obstacle on the floor is a real test of reactive footstep planning. Digit has to spot something small and moving, recalculate where to place each foot, and keep working—all without breaking stride or losing balance. That’s the same dynamic footwork Digit uses to navigate clutter and foot traffic on a real warehouse floor. [ Agility Robotics ] This is the most aggressive firefighting robot I’ve ever seen. [ DEEP Robotics ] Wait a sec, Dusty can print things on floors besides construction layouts? How is this not in every city, making sidewalks exciting and fun everywhere?! [ Dusty ] I am the first to admit that for US$4,900, the performance of the Unitree R1 is very impressive. But what is it going to do out in the world such that it will give you some sort of return on that investment? [ Unitree R1 ] Event cameras are extraordinarily powerful because they can see motion, but what if everything is moving because your camera is moving? Oh no! [ University of Zurich Robotics & Perception Group ] Can we understand whale behavior and language? Harvard SEAS Professor Stephanie Gil explains the possibility of understanding animal language and behavior using AI-driven robots and machine learning. With ongoing whale research and advancements in artificial intelligence, the potential for animal communication with whales could become a tangible reality. [ Harvard SEAS ] Rodney Brooks, founder and chief technology officer of Robust.AI, sits down with Forbes Assistant Managing Editor Kerry Dolan to discuss how he came up with the idea of the Roomba vacuum cleaner and the future of robotics. [ LinkedIn ] Here are a couple of interesting presentations from UIST 2025, including everyday objects that move around your home with a mind of their own and a project featuring teamwork between helium balloons and ground robots called Buoyancé. [ UIST 2025 ]

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Video Friday: Do Robots Even Need Legs?

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO IROS 2026 : 27 September–1 October 2026, PITTSBURGH Enjoy today’s videos! Eno is our first agentic robot: an AI agent and a general-purpose robot working as one system. It reasons, plans, and acts in the real world. Human in capability, not in form. Every detail with a purpose, reduced to what matters. Designed not to resemble us, but to extend us. Eno is built end to end at Genesis. [ Genesis ] Engineers from NASA’s Jet Propulsion Laboratory are field-testing advanced capabilities for potential future Moon and Mars rovers. In the Colorado Desert near Plaster City, California, teams used a prototype rover called ERNEST (Exploration Rover for Navigating Extreme Sloped Terrain) to test software for a potential future long-range lunar mission . The software enables the rover, developed at JPL, to operate autonomously and travel extreme distances with minimal intervention from human operators. ERNEST is a lot more capable than it may look; here’s some recent research showing the kinds of terrain it can handle: [ NASA's Jet Propulsion Lab ] Table tennis can produce moments that are difficult even for experienced players to anticipate… like when the ball clips the net and suddenly changes direction. For the Ace research project at Sony AI, these events were a key test of the system’s ability to operate reliably in unpredictable real-world conditions. Ace addresses this uncertainty by simulating counterfactual ball trajectories in real time. In the video, the green overlays show these alternative paths the system considers while planning its response. And check out some of these rallies that the robot has with Miyuu Khiara. [ Sony AI ] This video of an ANYmal deployment in a concrete plant is worth watching because it makes explicit how quadrupeds make money in inspection contexts : Among other things, “a cracked crusher foundation [was] caught before a week-long shutdown, avoiding roughly $630,000 in lost production.” That pays for a lot of robots. [ ANYbotics ] A lot of interesting footage here from GITAI’s prep for a robotic satellite servicing demo mission. The thruster test firing isn’t a robot, exactly, but it may be the coolest part. [ GITAI ] Anyone who’s tried to take a half decent photo underwater knows that it’s basically impossible, so let’s try and teach robots to cope. [ Bi-AQUA ] Thanks, Masato! Handling delicate, irregular or unpredictable objects is one of the hardest problems left in automation, and one of the most important. It’s what’s holding back the next wave of robots from doing more in the real world. That’s why we’re working with PSYONIC on a new approach. Their Ability Hand, worn by hundreds of people every day, captures real-world data on touch, pressure and grip. Our GoFa cobot brings the industrial-grade accuracy and repeatability to turn that human data into reliable robotic performance. [ ABB Robotics ] Sanctuary AI has achieved world-class performance on a complex wire plugging production task with a global Tier 1 automotive supplier. In this demonstration, Sanctuary AI’s Physical AI successfully performs a high-speed wire plug insertion task, achieving a validated task success rate of over 99.5% with a cycle time of just 2.54 seconds, meeting live production benchmarks established by the customer. WHY IS THIS STRESSING ME OUT SO MUCH? [ Sanctuary ] This video is quite obviously fake, but I suppose maybe there’s a market for extra beefy quadrupeds? Maybe? [ Kepler ] I cannot overstate how much I do not want any robot to look at what I’m wearing and then attempt to sell me things based on what it thinks it can guess about my personality or interests. [ MagicLab ] I am here for fed up robots learning how to move boxes by just kicking them. [ ATARI Lab ] Ah yes, very useful and very important robots that make me very uncomfortable. [ Paper ] I built GrowBot ( a ~6”, two-servo bipedal robot) that runs entirely on a $15 Raspberry Pi Zero 2 W, ~$100 in parts. An LLM drives it directly: it reads the raw IMU stream with no translation layer and narrates its own motion (“rocked side to side like a baby”), riding on a 50 Hz reinforcement-learning walk policy trained in sim and transferred to the real body. The idea here is to build an open course around this project, Brit says, “so everyone can experience physical AI right now in a low risk way.” [ GrowBot ] Thanks, Brit!

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Video Friday: Robotic Motion Discovery Reveals Unusual Behaviors

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO Enjoy today’s videos! We present MotionDisco, a framework that discovers contact-rich, long-horizon humanoid loco-manipulation motions from scratch, without relying on teleoperation or motion retargeting from human demonstrations. Some of the discovered behaviors are a little nutso: [ MotionDisco ] Not sure I’d say any of this is ‘effortless’ but those claws are pretty cute. [ DEEP Robotics ] It turns out running a workout class is a decent way to stress-test whole-body range of motion . Coordinating fluid movement across every joint at once–timing, velocity, balance compensation–is one of the harder control problems in humanoid robotics. [ Agility ] Our very own Gwendolyn Rak made a robotic shoulder-friend at Computer Human Interaction in Barcelona. Here’s a bit more about it: [ MIT ] At AIRoA, we’re bringing robots into real homes . Check out our exclusive first video to see how they work in our development hub and real-life household settings! The project aims to develop home robots that can assist people with everyday tasks and become long-term companions in daily life. In this video, we demonstrate Toyota’s Human Support Robot (HSR) deployed in real homes, where it assists residents with everyday tasks such as tidying rooms and fetching objects. [ AI Robot Association ] Thanks, Naoaki! MIDAS Hand is a fully open-source, tactile-sensor-integrated dexterous robotic hand platform for manipulation, teleoperation, and robot learning research. MIDAS stands for Modular low-Impedance Direct-drive Anthropomorphic Sensing Hand. [ MIDAS Hand ] Thanks, Jun Kim! This video presents a novel flight maneuver for a flying bipedal robot. During forward flight, the robot performs aerial braking by swinging its legs to adjust the orientation of foot-mounted thrusters. [ Paper ] Seems like a really good application for autonomy, tbh. [ Built Robotics ] In this timelapse, controllers on the ground are repositioning Dextre , our robotic handyman currently installed at the end of the Canadarm2. They used Dextre to unload equipment from the unpressurised Dragon trunk. Such a beautiful choreography to watch with Earth in the background! [ European Space Agency ] This video demonstrates how AI Sapiens learns and performs humanoid motions from video-based motion capture using only a smartphone camera, without professional motion-capture equipment. ROBOTIS plans to release an open-source motion generation and learning pipeline for AI Sapiens, enabling users to generate humanoid motions from video and bring them to the real robot. [ ROBOTIS ] NAO LIVES! [ Maxtronics ] Tumblenauts are a swarm of minimalist, bacteria-inspired robots designed for collaborative inspection of pressurized microgravity habitats such as the International Space Station. Unlike current intra-vehicular robots that rely on complex actuator-dense mechanisms for precise motion, the Tumblenauts use a stochastic run-and-tumble locomotion and collective cooperation inspired by bacterial colonies. [ Self-Organizing Swarms and Robotics Lab ] LUMOS Robotics Founder & CEO Yu Chao officially introduces Project EDGE — inviting global builders, universities, robotics labs, and creative technologists to explore the future of humanoid robotics together. To supercharge the global developer community, we are providing 100 complimentary LUMOS NIX robots to selected global partners. [ Lumos Robotics ] How do you progress from early childhood computational thinking to advanced high school robotics? Sphero’s product offerings are intentionally scaffolded to scale with students by building critical skills and concepts at every grade level. [ Sphero ]

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How JPL Keeps the 13-Year-Old Curiosity Rover Doing Science

Thirteen years ago last August, I was camped out in the Jet Propulsion Lab press room in Pasadena, Calif., waiting to see whether the Curiosity rover would survive its descent and skycrane-assisted landing on the surface of Mars. It did, and it was awesome . Since then, Curiosity (also known as Mars Science Laboratory) has traveled nearly 37 kilometers , drilled into and sampled 42 different rocks , and as of publication, has snapped nearly 763,000 photos . The fact that this robot is still hard at work , getting real science done at the age of 13, is absolutely incredible—not only is Mars an actively hostile environment for robots, but the only kind of maintenance that JPL engineers can do is to send very, very careful software updates. Nevertheless, the clever folks at JPL have managed to keep Curiosity safe, warm, mobile, and sciencing, despite well-worn wheels and less and less power every day. One of those folks is Alexandra Holloway , the assistant team chief for engineering operations for Curiosity, who spoke to IEEE Spectrum about keeping Curiosity roving, what its future looks like, and how JPL has used that experience to make rovers like Perseverance even more capable. How astonished should we be that after 13 years on Mars, Curiosity is not only still doing science, but actually getting more capable? Alexandra Holloway is the assistant team chief for engineering operations on the Curiosity Mars rover at the Jet Propulsion Laboratory. Alexandra Holloway Alexandra Holloway: I’m astonished! The longevity comes from a lot of ongoing work. It’s not just that Curiosity was built robustly; it’s also because we’re continuously putting in effort to ensure it can continue to have that lifespan. I think about all the different kinds of embedded systems there are, from cars to refrigerators, and none of them have the kind of longevity that we have with the rover. It’s mind-boggling, and it’s inspiring. Is the Perseverance rover , which is nine years younger than Curiosity, significantly different in terms of its hardware and software? Holloway: In terms of hardware, the rovers are actually very similar. Both use a RAD 750 processor and have the same amount of memory. However, Perseverance has an extra processor specifically for visual odometry, which allows it to drive autonomously. This difference reflects their primary mission designs : Perseverance was designed for driving long distances, while Curiosity is a mission focused on sampling as it goes. So, Perseverance’s onboard scheduling capabilities are there to optimize its driving. In fact, just last year, Perseverance surpassed Curiosity’s driving distance after only about three years on Mars. Curiosity Rover Memory and Software Fixes Do you have some examples of significant tweaks the team has made to keep Curiosity roving? Holloway: One of my favorites examples comes from a processor anomaly that happened on Sol 2172 [Ed. note: “Sol” is the term for a Martian day—about 24 hours and 40 minutes]. Curiosity has two computers, A and B. We landed on A, swapped to B due to a NAND memory anomaly early on (Sol 200) . For years, we were chugging along on B, until one day there was a problem—B booted up, but it couldn’t mount its drive partition. We’d never seen this before. To preserve B’s data, we swapped back to A, which we hadn’t trusted in two thousand Sols. A also had a degraded memory, with only two gigabytes of usable storage space instead of four. We painstakingly transferred data from B over to A and then down to Earth, and eventually we ran out of stuff we wanted to transfer, which was really good, because A then started acting funny in the same way it did on Sol 200—it was acting like its memory was coming unsoldered. That’s bad. We quickly swapped back to B, formatted it, and got it working again. The problem then became that we couldn’t trust A’s memory at all, but we needed a second computer as a “lifeboat” for diagnostics and transfers if B failed again. We realized we had one other place of memory: where we keep our flight software. We have four copies of the flight software (two current versions, and two older versions) in different banks of very small amounts of memory, just 32 megabytes each. What if we just jettisoned the old flight software copies and used that 64-megabyte NOR memory as our file system for computer A? So that’s what we did . It was so elegant! Computer A is operating with less than 1 percent of its original memory, but we can run a mission on it. A small mission, but we haven’t had to jettison any core capabilities. We can still drive, we can manage data, we can even theoretically do science. Everything works fine, just much slower and much smaller. That flight software release was even called “R-Hope “ because we hoped it would work. What are the constraints on Curiosity’s lifespan? Holloway: Our biggest hardware challenge is wheel wear . It looks like we’re driving on this sandy terrain with some rocks in it, and our intuition said that we could just drive over these rocks and they’d get pushed down into the sand and it would be no big deal. But what we ended up seeing was that those little rocks are actually the tips of giant boulders buried in the sand, and they’re razor sharp. Our wheels were getting ripped apart driving over them, especially our front wheels, so we started driving backwards . We also monitor consumables. We consider the number of times we move our actuators, that’s a consumable—Curiosity hasn’t taken a selfie in a while, and one of the reasons is that it’s really hard on the joint actuators. Our onboard memory is a consumable, but surprisingly, we’re not anywhere near our life cycle for memory. Our biggest consumable is power; we have an RTG , a nuclear power source, which decreases its output as it ages. Newer missions are flying Snapdragon [processors], but Curiosity’s RAD 750 is a power hog. One of the things that we’ve rolled out that’s going really well is a way of reducing the amount of time we spend with the computer powered on, by harvesting time when we finish activities early and going to sleep, which lets us turn off the computers and some of the heating. Another thing we’re looking at is doing stuff in parallel when we’re on, like being able to drive or use the arm while communicating with an orbiter. So power is decreasing, and that’s causing us to do all this parallelism work and become more efficient and nuanced in the way we operate, but we are not having any degraded science output at this time. Our wheels are still going, our arm is still okay for now, knock on wood. I would say maybe the bottleneck is budget. Curiosity Rover’s Impact on Future Mars Exploration What have you learned from Curiosity that will improve future missions? Holloway: As an embedded flight software person, I think about how we can change, add, or modify software capabilities during the mission. There’s definitely a sweet spot for loading and patching flight software—some of these concepts were pioneered on Spirit and Opportunity and then inherited by Curiosity and Perseverance, making it easier to understand and change the software. Some of the things that I wish we had now on [the Mars Science Laboratory] include a better understanding of where our power is going. I want to see how much power each component is drawing every minute, so that we could architect a software system that could balance loads better. We have some of this information that was built in by the engineers who designed the rover, but as an operator, I want something slightly different. So if I were building a mission, I would have those discussions earlier, and get operators into the room to say, “what do you want your data products to look like?” The key takeaway for designing future missions is to talk to all your users early in the design process—it needs to happen upfront. What does Curiosity’s long-term future look like? Holloway: That’s a conversation that happens, and it’s a really delicate one. We have a lot of science instruments, and a lot of them have to do with contact science and sampling and rely on the arm. If we lose the arm, what science can we still do? Well, we have a lot of remote sensors too, like cameras, environmental sensors, and radiation sensors. All of these things are important for the future of space exploration and humans on Mars. From a power perspective, our RTG is projected to start degrading science output in the sixth extended mission, but we’re going to be fine through 2035, and potentially even beyond that. So, we have a long and exciting future ahead of us. We need to figure out the best way of operating within our constraints, but we’re still kicking.

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Video Friday: Watch This Running Robot Not Fall Down Stairs

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO Enjoy today’s videos! It’s been a while since a humanoid robot video actually impressed me, but the beginning of this does. Hard to know how much of that recovery was luck, though. [ DEEP Robotics ] When you’re very confident in your MPC-based balance controller... I feel you, buddy. And thanks for posting this. We’ve all been there, in one way or another. [ DARoS Lab ] GENE01 designed from scratch and sent to batch production. Two scalable lower bodies. Physical AI deployed for motor control and world-action modeling. All in three months. Generative Bionics is running. [ Generative Bionics ] Alex, the newest humanoid robot built entirely by ‪IHMCRobotics‬, takes its first steps outdoors! This was a significant milestone for our team, especially because Alex is the first humanoid robot developed entirely by IHMC Robotics to venture outside the lab. These outdoor trials were conducted in preparation for a demonstration in Maryland, where Alex later successfully walked completely untethered. [ IHMC ] Built on the Enlight platform, Flexiv MICO is a compact dual-arm system engineered for safe, seamless collaboration in any workspace. [ Flexiv Robotics ] Is it weird that I’m jealous that robots can have feet that are swappable? [ Boston Dynamics ] Midweek at ICRA 2026. Cable-climbing robots that work as a squad: CCRobot-S is a team of robots with reconfigurable cable-driven manipulation that collaboratively inspect and maintain long-span bridge stay cables. Parallel operation for speed, morphological reconfiguration for reach. [ IEEE Transactions on Robotics ] I would love to know the story behind this odd choice of hat. [ ROBOTIS ] How did Atlas learn football–and why? Go behind the scenes of School of Football and discover a glimpse of the Next of robotics. What I really want to know is, what kinds of things is it possible to do in football (soccer ) when your robot’s joints are not constrained by biology? [ Boston Dynamics ]

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Video Friday: Extreme Omnidirectional Robot

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO Enjoy today’s videos! What is the right number of legs for a robot? Two? Four? No, the answer is obviously all of them. All of the legs. [ Argus ] Sigh, yet another skill that I as a soccer-playing human should have but a robot has instead: the rabona. [ Boston Dynamics ] Robots are rapidly becoming part of our everyday lives, from drones and industrial machines to home assistants and humanoid robots. As their presence continues to grow, an important question arises: how can we choose the right robot—not only in terms of performance and cost, but also in terms of sustainability? This video introduces the Eco‑Score for Robots, a new approach to evaluating the environmental impact of robotic systems. Just as eco-labels help consumers make informed choices in other industries, the Robotics Eco‑Label provides a clear and transparent way to assess how sustainable a robot truly is. [ Robotics EcoLabel ] Thanks, Bram! Uh oh, five-fingered hands . [ Agility ] Robotic manipulation has come a long way since the 1990s. We’ve gone from the two-ball paddle juggling robot to AthenaZero, who can juggle barehanded using onboard vision feedback. By moving away from task-specific passive end-effectors such as cups or paddles and using multi-fingered hands, it can transition between a wide range of patterns including cascade, half-shower, tennis, shower, and box. There needs to be a robot circus show already. [ Robotics and AI Institute ] Zero legs. One hat. $13k. [ Astribot ] From its elegant design to the advanced technology powering every step, Luna is more than a machine—it’s a leap into the future. [ LimX Dynamics ] Thanks, Jinyan! You got a quadrotor in my quadruped! No, you got a quadruped in my quadrotor! [ MARS Laboratory ] A human hand, a robot’s arm—together tracing circles of trust and precision. No missteps. No hesitation. Just pure, algorithmic grace. [ UBTECH ] Low gravity planetary exploration with a quadruped just looks like fun. [ Autonomous Robots Lab ] Here it is, that robot Kool-Aid that everyone seems to be drinking. Including me! [ Generalist ] Don’t shoot Mini Pupper! [ MangDang ] We show here the ARISTO (Anthropomorphic, Robotic, Integrated-Sensing, Tendon-Operated) Hand. Developed in collaboration with Sony Group Corporation, this research platform is engineered to address the complex requirements of manipulating small, thin, and fragile objects. [ University of Texas Human Centered Robotics Lab ] Okay but did you really have to call it the T800? [ EngineAI ] Moby shows what useful mobile manipulation looks like in the real world: picking up, carrying, and placing adaptable payloads. The video shows payload handling across increasing crate loads, including a 50.3-lb load, while maintaining balance, control, and mobility. This is the kind of capability that matters outside the lab—moving real objects, in real spaces, with practical reliability. [ Noble Machines ] What does it take to make a robot look human? Harvard SEAS students Hailey Block, Henry Tavistock, and Evan Crowley created “Hollow Minds,” a pair of animatronic heads capable of speaking, blinking, tracking movement, and displaying lifelike facial expressions. [ Harvard University ] The longevity here is impressive, but the obvious question here is why the heck you’d ever do this task with a bipedal humanoid robot. It also doesn’t seem to have any error recovery, which is obviously fixable, but highlights the fact that real humans are versatile and humanoid robots are not. [ Figure ] Kacper Nowicki, CEO and Co-Founder, Nomagic, recently sat down for a deep dive into the “humanoid vs. purpose-built” debate during a panel discussion at the Web Summit in Vancouver 2026. [ Nomagic ]

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Video Friday: Atlas Versus a Fridge

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO Enjoy today’s videos! Just months after its debut, Atlas is proving why it is the world’s most capable and dynamic humanoid robot, ready for real work. Lifting a mini-fridge is a feat of strength, but the true breakthrough is in the underlying reinforcement learning and controls systems. The robot is learning to navigate real world adaptability: handling heavy objects by bracing and accounting for the mass and inertia; using whole-body control, not just hands to maneuver; and demonstrating superhuman range of motion and balance. This marks a critical shift in robotics where humanoids move beyond the lab and into dynamic industrial settings. Watching Atlas move a fridge may be less impressive than whatever the heck it does at 4:10. [ Boston Dynamics ] SpikerBot is a robot you teach by wiring neurons, not writing code. Drag spiking neurons in the app, connect them to sensors and motors, then press play. It moves, reacts, and changes behavior based on the brain you built. Already funded on Kickstarter with a robot kit starting at $219. [ Kickstarter ] via [ Backyard Brains ] Thanks, Greg! Wheeled-legged robots, which have wheels at their feet and achieve high mobility by coordinating wheel drive and leg drive, have been developed. In this paper, we address the problem of how to draw out the potential task-execution capability of the legs by freeing them from the roles of locomotion through external body support. [ WiXus ] from [ JSK Robotics Laboratory ] via [ ICRA 2026 ] A very clever idea for electronics-free multi-dimensional touch sensing. [ Nature Communications ] Using external voice commands, G1 is directly controlled to generate a wide range of actions in real time. This video was recorded in a single take, with on‑site audio recording. [ Unitree ] Hummingbirds are impressive flyers, and advancements in high-speed photography, instrumentation, and measurement techniques have revealed much about their aerodynamics, flight behaviors, and wing and body kinematics. However, comparatively less is known about their natural flight dynamics, which is the relationship among a bird’s flight velocities, the control actions of its wings, and the acceleration of the bird in flight. To investigate this, at the Advanced Vertical Flight Laboratory we have designed, built, and flight tested a biomimetic robotic hummingbird on which is implemented the same techniques for flight control as observed in hummingbirds. [ Advanced Vertical Flight Laboratory ] I guess if you’re going to make a robot dog , it’s only fair to give it the ability to frolic in the water. [ MagicLab ] The original automated layout robot — the one that showed up when the construction industry was pretty sure robots were lame, and proved otherwise. It has printed millions of square feet of layout across thousands of projects. It built an entire category of construction technology. The category of: Stuff That Actually Does Helpful Work on Real Jobsites. But FieldPrinter 2 is here. It’s faster, tougher, smaller, and smarter. So for FieldPrinter 1, it’s time. Time for a quiet retirement. A mug. Maybe a plaque... BUT NAY, good knight! Thou shalt expire in a blaze of thunderous glory!! [ Dusty Robotics ] Here’s an interesting idea for an inflatable monocopter drone . [ AIRLAB ] Meet the Lynx S10—a compact all-terrain robot built to deliver industry-grade performance in a lightweight form factor under 20kg. [ DEEP Robotics ] Noble Machines builds general-purpose robots for heavy industry, supporting people with the most hazardous and physically demanding tasks. Attendees at NVIDIA GTC 2026 witnessed the power of autonomous industrial work with Noble Machines Moby. [ Noble Machines ] I’m sorry but LEGO bricks should be for humans only. [ LimX Dynamics ] Need a robot that can go places? Huskies were around way before legged humanoids, and I bet they’ll be around way after, too. [ Clearpath Robotics ] I know this little dude is just a research platform at Disney, but I still want one to be my friend. [ Paper ] In March 1982, General Motors announced a rapid and aggressive conversion to robotics. By 1990, GM wanted 14,000 robots in their factories doing everything from painting to welding to assembly. Nowadays, we dream of robots in the factories, doing everything end to end. In the dark. Lights out. Guess what, GM dreamed the same 40 years ago. And they spent an estimated $60 billion to try to make it reality. In today’s video, we look at General Motors and their dreams of the automated, all-robot factory. [ Asianometry ]

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Video Friday: Heavy Robotic Machinery Operates Itself

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO Enjoy today’s videos! Bulk material handling is a critical, labor-intensive operation across various industries, traditionally performed by human operators using heavy hydraulic manipulators equipped with free-swinging, underactuated grippers. This work presents the first complete autonomous material handling solution deployed on a real-world 40-ton material handler. [ ETH Zurich ] I don’t want to minimize this bedroom tidying by Figure (although I suppose I’m going to), but in the context of doing a task like this in place of a human, it really illustrates what these robots are comfortable with, and what they’re not. [ Figure ] Give me this over videos of robots doing backflips any day. [ Hello Robot ] Okay but can it get them out of the can? [ Generalist ] The world’s first production-ready manned mecha. It can transform. It’s a civilian vehicle. It weighs ~500kg with you inside. [ Unitree ] Curious about what happens when street dance meets embodied AI? From smooth choreography to dynamic flips, NIX is exploring movement, rhythm, and real-world interaction through embodied AI. We’ll make NIX available—FOR FREE!—to selected partners from global universities, robotics labs, and creative technologists. [ Lumos ] Thanks, Ni Tao! We introduce and open-source the Unified Autonomy Stack, a novel solution for resilient autonomy across aerial and ground robot morphologies. The architecture combines multi-modal perception, multi-behavior planning, and multi-layered safe navigation to deliver mission-level autonomy across diverse robot morphologies. It fuses LiDAR, radar, vision, and inertial sensing to enable robust localization and mapping, vision-language-based scene reasoning, multi-behavior planning, and layered safety through map-based avoidance, deep learned policies, and control barrier functions. The system supports GNSS-denied navigation in perceptually-degraded environments, exploration, object discovery, and inspection, and has been validated on multirotor and legged robots in challenging settings, demonstrating resilient performance. [ NTNU ] Thanks, Kostas! Cassie WAS the best robot! The next video better be a Digit Centaur. [ Agility ] Any robot doing anything consistently over a long period of time is impressive. Having said that, you want to be very careful about claiming that any robot operates at “human performance levels,” especially in a somewhat complex manipulation task, because humans are very, very good at stuff like this. [ Figure ] Robust.AI co-founder & CTO Rodney Brooks , ranked #44 on the Forbes 250 America’s Greatest Innovators list, sits down for a Q&A ahead of his panel discussion at the Forbes America Innovates event in San Francisco. We asked him two questions: What makes innovation in robotics such a challenge? What does the current surge in AI mean for robotics today? [ Robust AI ] This is one of the best robotic research videos I’ve ever seen, and don’t worry, according to the credits it’s not AI. And make sure to watch after the credits! [ Nature ] EFGCL is a guided reinforcement learning method that efficiently enables highly dynamic motions through the use of assistive forces. In this work, we successfully achieved several dynamic motions, including jumping, backflips, and lateral flips. [ EFGCL ] Thanks, Keita! Legged robots: helping farmers one vegetable at a time. [ University of Southern California ] Humanoid robots promise general-purpose assistance, yet real-world humanoid loco-manipulation remains challenging because it requires whole-body stability, dexterous hands, and contact-aware perception under frequent contact changes. In this work, we study dexterous, contact-rich humanoid loco-manipulation . [ Touch Dreaming ] More than just technology, KATA Friends is a lifelike AI companion designed to see your world, feel your touch, and understand your heart. With expressive movements, evolving emotions, and natural conversations, Noa and Niko both grow alongside you to become a presence uniquely yours. From curious head tilts and playful reactions to ever-changing eye expressions and a soft, innocent voice, every interaction feels warm, personal, and alive. [ SwitchBot ] I really hate to say this, but despite how cute it is, Aibo may be showing its age. [ Aibo ] One of the biggest challenges in robotics right now isn’t the hardware. It’s data. While many data collection methods are effective, handheld data collection can create a diverse dataset of environments, conditions and strategies for completing manipulation tasks. The Koala platform: co-designed the handheld grippers and robot grippers around the same linkage mechanism, same degrees of freedom, and same force transmission. The human feels through the linkages what the robot will feel through its actuators. [ Robotics and AI Institute ]

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Hello Robot Sets the Standard for Practical, Safe Home Robots

Many roboticists (and at least one robotics journalist) have been seduced by the dream of a robot butler. And the rampant popularity of videos showing humanoid robots doing household tasks in improbably clean kitchens and unrealistically tidy bedrooms suggests that we’re not the only ones interested in a robot that can do our chores. But for all kinds of reasons , legged humanoids are not yet ready for industrial or commercial applications at scale, and home applications (if people even want them ) are, I would argue, even farther away. Even so, ludicrously well-funded humanoid robotics companies are now ramping production while explicitly promising that their robots will be doing ‘housework .’ So what about that robot butler dream, then? It still exists! All you have to do is forget about legs, arms, hands, faces, and focus on what really matters: mobility and manipulation. This is what Hello Robot’s Stretch robot is unapologetically all about, and the newest version being announced today, Stretch 4, is closer than ever to a robot that could safely do practical work in the home at an accessible cost. Hello Robot says Stretch 4 is “built for the real world.” Hello Robot “With Stretch 4, we wanted to make the transition from a research platform to something that is truly deployable,” explains Aaron Edsinger , Hello Robot co-founder and CEO. This version, while ready for research and enterprise customers now, is designed for pilot deployments to help Hello Robot understand how to scale in the home. “This has been our most difficult design process,” adds co-founder and CTO Charlie Kemp . “We had a lot of fear of ‘second-system syndrome,’ where you add all the features you didn’t get to initially and end up with a monstrosity. But since we founded the company on making simple, minimalist robots, every time we added complexity it was an emotional challenge. Navigating that fear resulted in a nice compromise that sits in a great spot, rather than being a maximalist humanoid.” Stretch 4 Upgrades The biggest change from the previous version of Stretch is the addition of an omnidirectional base, meaning that the robot can translate in any direction without having to turn first. This makes it much easier to control (especially for novice users), but omnidirectional bases are significantly more complicated to design and build. What ultimately made it possible for Stretch were new types of omnidirectional wheels developed for powered wheelchairs, along with a solid six months of focused development by Hello Robot. A redesigned sensorized head gives Stretch more options for teleoperation and autonomy. Hello Robot Stretch 4 also ditches the cute little pan-tilt head for a more complex sensor suite with a much wider field of view. “We started out wanting to use lots of cheap cameras to keep costs low, like Tesla does,” Edsinger told us. “But we ended up with an approach closer to Waymo’s: the richer and more reliable your data, the safer and more intelligent the robot can be.” There are a pair of hemispherical lidars, Luxonis cameras for vision and navigation, and a wrist-mounted depth camera for manipulation. The robot’s primary system runs on an Intel NUC 15, plus an NVIDIA Jetson Orin NX for researchers to play with for visual processing or AI. Philosophy on Autonomy Hello Robot’s general philosophy on autonomy is to have a human in the loop, but that can take many different forms ranging from direct control to purely supervisory control. The robot will ship with a baseline of autonomous capabilities that include mapping, navigation, and self-charging, along with demo-ready features like autonomous grasping. But unlike most other robotics companies, Hello Robot isn’t looking to use their hardware to collect a stupendous amount of data in the concerningly vague hope that commercially viable autonomy will follow. “Stretch has huge advantages in safety, cost, and capability,” Kemp says. “I’d much rather be the platform that foundation model developers target.” Edsinger agrees: “We do want to partner with foundation model companies to explore things like dexterous in-home manipulation, but we aren’t the ones to build those foundation models.” In-Home Pilots While earlier versions of Stretch were primarily for research, Kemp tells us that Stretch 4 has been explicitly designed to be piloted in the homes of people with severe mobility impairments. Hello Robot will be happy to sell you one (or lots, I’m guessing) for commercial or industrial applications, but the broader goal with Stretch 4 is to use remote testing and in-home evaluations to work towards a robot that’s useful and reliable enough that it can provide consistent daily value for disabled users. A holonomic base and an extendable arm make for a capable robot without the complexity. Hello Robot Part of why I’m optimistic about Stretch finding near-term success in this role is precisely because it’s not a humanoid. One of the primary arguments for humanoids is that they’re worth pursuing because they can better operate in environments designed for humans, where legs and five fingered hands are tangible advantages. But those very same environments often exclude an entire subset of humanity—a subset of humanity that we will all likely join at some point, because the best that any of us can ever say is that we are not disabled yet . Why Not Humanoids? A key partner for Hello Robot throughout the Stretch development process has been Henry Evans . Evans is paralyzed and cannot speak, although he can use a computer (for controlling robots, among other things) and type at about 15 words per minute. I spoke with Evans about his thoughts on the idea of a humanoid assistive robot, compared to a robot like Stretch. “The question is: what benefit does a bipedal robot offer to a person who can’t walk?” Evans asks. “Their entire environment has been modified to accommodate wheeled conveyances. Automobiles don’t have legs, and neither should home robots. Wheels are cheap, stable, precise, require very few controls, and don’t have to be invented.” Henry Evans has been testing a Stretch 4 as a home assistive robot. Hello Robot Evans also points out that humanoids can require the simultaneous control of dozens of degrees of freedom. “A paralyzed person who can’t talk (like yours truly) can control maybe one or two joints at a time with today’s control mechanisms, if they are lucky.” Evans believes that AI, along with Brain Computer Interfaces (BCIs), show promise for dramatically increasing what he can do when it comes to motion. “Remember, though, a paralyzed person has no movements to mimic, so until a perfectly tuned BCI gets here and facilitates a true humanoid body surrogate, I don’t think it will work. And even then, I don’t see the advantage of legs for assistive care robots. I am willing to be proven wrong, though, and will test-drive almost anything once, so bring it on!” Kemp and Edsinger, who have many decades of humanoid experience between them, feel similarly. “There are applications where the human form is fundamental,” says Kemp. “But for many applications, the value of the human form is unclear or even problematic. Jumping to the conclusion that robots must be humanoid means missing opportunities to take advantage of the structured indoor environments that we’ve already created.” Georgena Moran and her sisters tested Stretch 4 at the California Academy of Sciences Museum, allowing her to interact with the exhibits from home. Hello Robot And of course there’s the question of safety, which Evans brings up. “My caregivers and I have been testing robots in my home to assist us for about 15 years, and the very first concerns are: where is the emergency stop and how do you activate it? It gets used surprisingly often. The thing is, when a wheeled robot gets emergency stopped, it freezes in place. When a bipedal robot gets run-stopped, it collapses on anything under it, including the patient.” Kemp agrees. “The safety aspect of humanoids in a home freaks me out. I don’t know how someone can confidently think about safety with a humanoid in a home.” Robots for Sale However you feel about humanoids, here’s one more reason why Stretch feels like a much more realistic solution for in-home assistive robots right now: You can actually buy one, and at $29,950, it’s very affordable, as mobile manipulators go . Edsinger and Kemp are planning to leverage in-home Stretch 4 pilot deployments to make the next version of Stretch the one that can be commercially sold for home assistance. At the rate that Hello Robot has been releasing new hardware, that could easily be within the next year or so—and my guess is that Stretch 5 is very likely to be the first practical, affordable, assistive robot for home use. It may not look like Rosie, but it promises to be safe, and it works.

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Video Friday: AI Gives Robot Hands Human-Like Dexterity

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO Enjoy today’s videos! Introducing GENE-26.5—the first AI brain to give robots human-level physical manipulation capabilities. Cooking a full meal. Cracking an egg one-handed. Conducting lab experiments. Wire harnessing. Even playing the piano. Tasks that were impossible for robots. Until now. [ Genesis AI ] via [ TechCrunch ] This is Labububot—one of the rarest monsters on Earth. Twelve Labubu heads are reconstituted into a single spherical form: a Frankenstein’s Monster of pop culture iconography. Labububot is a playful critique of social robots , and a question made physical—what do the monsters we make reveal about the monsters we are? [ MIT Media Lab ] Watch Spot crouch, jump, climb boxes, and leap across gaps, controlled by a neural network trained with reinforcement learning (RL) and multi-expert distillation. [ Robotics and AI Institute ] Good, now there is a robot that can take over exercise for me. [ Kepler ] Additive manufacturing has become an enabling technology, but existing techniques are not capable of directly 3D printing high current electromagnetic actuators due to material and design limitations. In this work, a novel 3D-printable, multi-layer, wave-winding topology is created for high efficiency electric motors. [ Sensing Technologies Laboratory ] NASA is pushing the limits of flight on Mars —by spinning helicopter rotor blades so fast, they’re breaking the sound barrier. During recent tests at NASA’s Jet Propulsion Laboratory, engineers accelerated the tips of next-generation rotor blades beyond Mach 1 inside a special chamber that simulates the atmospheric conditions of the Red Planet. [ NASA Jet Propulsion Laboratory ] Balancing commercial goals and robotics research can be tricky, but with Atlas we’re making it work. [ Boston Dynamics ] Open Duck Mini is an open-source version of Disney’s BDX droids, and you can play with it in your browser. [ Open Duck Mini Viewer ] Thanks, Masato! Automated inspection of steel structures using magnetic climbing robots can reduce costs and improve safety, but many such structures feature interior corners that are challenging for wheeled or tracked robots to traverse. We present the first magnetic-wheeled robot to use X-ray fluorescence for steel structure inspection, Sally, capable of overcoming all interior corner transition types, traversing small obstacles, and maneuvering in tight spaces. [ Robomechanics Lab ] I don’t know what this is, but it’s coming soon from SwitchBot. [ SwitchBot ] You probably know the answers to these questions already, but this ELI5 from Aaron Ames is still fun. [ Wired ] Jim Fan, who leads the embodied autonomous research group at Nvidia, returns to AI Ascent to argue that robotics is entering its end game—and that the playbook is already written. [ Sequoia ]

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iRobot Founder Wants to Put a Robotic Familiar Into Your Home

Two years ago, Colin Angle stepped down as CEO of iRobot , the company that he co-founded and the most successful home robot company the world has ever seen. Angle almost immediately founded a stealthy new “physical AI” company called Familiar Machines & Magic (FM&M), which in short order managed to attract a combination of exceptionally talented robotics folks, including Morgan Pope from Disney Research , which got us very curious. Today, Familiar Machines & Magic is announcing its first robot, a “physically embodied AI system designed to perceive, adapt, and interact with people in ways that feel natural and consistent,” the press release says. This robot is not a toy, and it’s not specifically for kids. Rather, it’s for adults to purchase for themselves and their families. It will get to know you, seek you out for attention, and actively help you to positively pursue an idealized routine in your life. Intended for adults, Familiar is pet-like in that it will seek you out for attention. Familiar Machines & Magic Here are the (limited) technical details from the press release: The first Familiar is a quadruped, specifically designed for human-robot interaction, with 23 degrees of freedom enabling both lifelike movement and expressive behaviors. The Familiar is covered with a custom touch-sensitive coat, a vision system, and a microphone array and audio system, to support rich interactions. Its onboard edge AI stack is powered by a custom small multimodal model optimized for social reasoning, combining vision, audio, language, and memory to create socially responsive behaviors in real time. FM&M CEO and co-founder Colin Angle tells us that this first prototype Familiar is designed to look like a sort of highly abstracted bear. It’s very deliberately nothing like a dog or a cat, following the successful strategy of other social robots like Paro and Pleo —if you can’t connect the form factor to an animal that you have direct experience with, you won’t bring expectations to your interactions with the robot. What Does it Do? “Our goal is to position this as a robot familiar that lives with you and helps reinforce healthy routines,” Angle says. He explains that thinking of a Familiar like a pet is a strong analogy, but pet-like also undersells what the robot can do. The Familiar behaves a little more like a service animal, in the narrow sense of being able to recognize activities and intervene to motivate you to do more or less of them, as the case may be. One easy example is screen time—the Familiar can note how much time you spend on your phone, and if it’s too much, it can actively try to engage you in other activities, including taking it for a walk outside. “The idea,” says Angle, “is that you can have a bit of technology in your home which is hyper-loyal to you, gets to know you, helps you figure out an idealized routine, and then plays a positive role.” Spending too much time on your phone? Familiar can help with that. Familiar Machines & Magic Cramming this amount of intelligence into a robot that you can take for a walk outside (at regular human walking pace) is extremely ambitious. I asked FM&M’s creative director Morgan Pope what made him feel like a robot like a Familiar was possible, with enough confidence that he was willing to leave Disney Research to join the startup. “ Two recent advancements made it feel tractable,” Pope says. “First, seeing Disney’s bipedal robots walk flexibly over various terrain using reinforcement learning proved you can execute dynamic motion without needing perfect, zero-backlash actuators or crazy expensive hardware. And second, while I am often skeptical of generative AI hype, it is a perfect fit here because it excels at creating the plausible assumption of intelligence, which helps the character feel coherent and lifelike.” The Challenge of Social Home Robots As a social home robot, the Familiar will have quite a lot of work to do to single-pawedly reestablish a category that burned itself out between 2012 and 2019. A series of high profile and very well funded startups including Anki , Mayfield , and Jibo were not able to sustain social home robots as a business, primarily because of a struggle with longer-term engagement. It’s not enough for a robot to be cute and charming in the short term; it has to continue enthralling its users or at least providing value after the initial novelty has worn off. In other words, a flashy demo is arguably counterproductive, which is a real problem, since robots excel at flashy demos. Part of the value of Familiar is that it will help you establish healthy routines. Familiar Machines & Magic “It’s about creating the right expectation and delivering on that expectation,” says Angle. “Familiars live in your world and play by your rules, and if you don’t find yourself hanging out with it, petting it, and engaging with it, then we haven’t succeeded.” In what is very much not a coincidence, the term ‘familiar’ really is the best way of thinking about this robot—a sort of vaguely magical non-human entity that has some amount of independence but whose existence and motivation are fundamentally tied to its human. “This isn’t trying to be a replacement for a real friend,” Angle explains. “It’s artificial life that lives in your world, has its own personality and goals, and has a special link to its guardian where it wants attention and wants its guardian to be active.” Creating Long-Term Value This philosophy is a key differentiator for FM&M. A Familiar is more than a companion; it has long-term objectives that it’s trying to fulfill to improve your life in a targeted way, says Angle. It’ll attempt to connect with you socially to encourage you to spend time with it in service of those goals, but the goals are the end, er, goals, rather than just the social connection itself, which was the primary draw of the previous generation of social robots. “Within a few days of bringing your Familiar home,” Angle tells us, “it’s figured out what its role in your life is. It’s trying to reinforce a healthy routine, whether that be summoning people to dinner or cuddling up while you watch TV, or greeting you when you get home. And then the way you sustain that relationship is by having it evolve, with both characters playing an active role—you’re also helping it with the things required to keep a robot operating.” Human-Familiar Interaction The temptation to leverage recent advances in AI to make a robot like a Familiar talk, especially in the context of regularly interacting with humans in pursuit of specific goals, must have been overwhelming. But to their credit, FM&M managed to resist. “I don’t believe that the technology exists today for AI to talk to humans in a safe, responsible fashion,” Angle explains. Consequently, a Familiar does not currently speak, although it does make sounds, and has plenty of other ways of communicating. “Through careful design, you’d be amazed what you can powerfully convey using a tail, wiggly ears, blinking eyes, and a brow that can be happy, sad, angry, or annoyed,” Angle says. This will likely resonate strongly with dog owners, somewhat less strongly with cat owners, and only very slightly with reptile owners like myself. Familiar is capable enough to keep up with you on walks outdoors. Familiar Machines & Magic Going the other direction is more complicated. Those same recent advances in AI mean that a Familiar can very likely understand everything you say and obey you perfectly, if it chose to. But doing so would break the illusion that the robot has its own desires and goals and personality, so FM&M had to be careful. “The way we’ve trained it from an AI perspective is really cool,” Angle explains. “We’re using a tableau of speech and vision inputs presented to a small multimodal model trained on stories, and for a given tableau of inputs, it goes through a generative process to decide at a high level what it is going to do. That decision is handed to a behavior engine which builds out those behavior trees into goals and drives a reinforcement learning unified motion model. There is nothing fully deterministic about your Familiar’s behavior; it truly tries to live its life with a variety of personality-driven emotions.” Safety at Home A Familiar is not a big robot, as robots go, but it’s not exactly small, either. And as something with legs, there’s always a concern about what happens if it falls over. “Its low center of gravity helps immensely,” says Pope. “If we pull power, it collapses downward safely rather than tipping over. Furthermore, it is wrapped in soft rubber, fur, and padding, so even if a leg impacts you, it won’t have a lot of force behind it.” Interestingly, FM&M is also leveraging the ‘character experience’ to mitigate risks to both robot and user. “We can use emotions to communicate hazards effectively,” explains Pope. “For example, if someone carries it somewhere high or puts it near an open flame, the Familiar can act visibly scared to directly communicate that it doesn’t like the situation.” While not a toy or specifically intended for children, Familiar can provide gentle, warm attention to your family. Familiar Machines & Magic Besides physical safety, social robots must also consider emotional safety. The better job you do emotionally connecting with people, the more responsibility you have to make sure that those connections are positive. “We take this very seriously,” Pope tells us. “We must follow a ‘do no harm’ philosophy, ensuring we don’t trigger unhealthy dependency or monopolize people’s attention the way a phone does. We are designing carefully to ensure the overall impact remains positive and never crosses the line into harm.” Additionally, the Familiar’s AI runs onboard the robot, and the robot does not stream private data to the cloud. It will, in fact, run just fine if you disconnect it from the Internet entirely, although you’ll lose access to any new features that come out. Managing Expectations Alongside the many engineering and HRI challenges that FM&M is having to manage is one other challenge that, in the near term, sounds rather dull but may be the most challenging: marketing. The company obviously has to promote this robot, but there’s a real danger (which has had dire consequences for many robotics companies in the past ) of selling an idea of what the robot could be rather than the reality of what the robot actually is . From speaking with Pope, FM&M seems to understand that robots have always been the most successful when the experience or task is incidental to the robot itself—in other words, what’s most compelling is what the robot will do , rather than the fact that it’s a robot. “The best way to understand a Familiar is that we are not building a robot; we are building a relationship,” Pope explains. Whether in the context of locomotion or relationships, we can be absolutely certain that a robot of this level of sophistication is not going to do what it’s supposed to every single time. Fortunately, the folks at FM&M have been building robots for long enough that they’re prepared for this. “We’ve explicitly tried to design it to motivate forgiveness,” Angle tells us. “This is not a precise robotic entity in its motion or dexterity. It’s supposed to be imperfect, but it’s going to get some of it right. By actively working to manage expectations to a place we can achieve, we want consumers to appreciate what it can do.” What customers expect, what they appreciate, and how much forgiveness they’re willing to bestow is for better or worse highly dependent on how much a Familiar will cost. “For the cost of ownership of something like a pet, you’re getting something that can help you live a healthier life, feel attended to, and provide social benefit,” Angle says. This could mean many things, depending on the pet, but one source puts the low end of the monthly cost for a cat at around $65 per month, with a dog somewhat more expensive at closer to $100 per month. FM&M’s press release stresses that today’s announcement ‘is not a commercial product launch,’ and specific pricing and a timeline will come later. A Future Platform While it’s much too early for us to be speculating about what the future might hold for FM&M’s robots, Angle is of course already thinking about other places where Familiars might be at home. “This first robot is meant to be a platform with general appeal and an opportunity to specialize into things like elder care and parental support,” Angle says. “From the ground up we are designing machines focused on human connection, and the underlying technology can further generalize into other form factors.” This will require the Familiar to find success, and it’s important to reiterate how much of a challenge this will be. A legged robot, designed for human interaction, in the home—everything about what FM&M is doing is hard. Because of his experience launching and leading iRobot, Angle is one of the very few people with the experience to really understand this, but his excitement and optimism about the Familiar is undiminished. “Do we know exactly how it’s going to land? I don’t,” says Angle. “But do I think it’s going to work? Absolutely. We’re going to find out, with a mission and goals that are noble at heart.”

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Video Friday: Figure, 1X Ramp Up Humanoid Robot Production

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN FRANCISCO Enjoy today’s videos! Figure is now able to produce 55 robots per week, which will be “allocated to internal research and development groups, data collection, efforts for robots to perform end-to-end housework, and commercial use-case development.” Er, that seems like a lot of robots to be making when commercial use cases are still ‘in development,’ doesn’t it? [ Figure ] The opening of the NEO Factory in Hayward, California marks a fundamental shift in humanoid robotics: America’s most vertically integrated robot factory has now begun full-scale production, bringing end-to-end manufacturing of NEO under one roof. Spanning 58,000 square feet and employing over 200 team members, 1X designs and builds every critical component in-house—motors, batteries, transmissions, sensors, structures, and final assembly—enabling faster iteration, superior safety, and true American scale. With the first robots already coming off the line and consumer shipments planned for 2026, this is the critical milestone that turns the vision of abundant, general-purpose home robots into reality. Scale will fix everything...? [ 1X ] Unlike statically stable robots, a dynamically balanced robot can shift its center of mass to accommodate loads without tipping over, so we like to see just how far we can push our software. Getting Digit to stand on one leg pushes the limits of our sim-to-real pipeline training methodologies—even the slightest model mismatches can lead to instability. [ Agility ] In this work, we develop a tactile-enabled whole-body humanoid manipulation system for stable, dexterous, contact-rich real-world manipulation. Our system combines VR-based whole-body teleoperation, an RL-based lower-body controller, dexterous hand retargeting, distributed tactile sensing, and a multimodal policy called Humanoid Transformer with Touch Dreaming (HTD). [ Humanoid Touch Dream ] Thanks, Yaru! Originally posted 2 years ago, “Can I Have a Pet T-Rex?” is a short interdisciplinary portrait documentary featuring paleontologist and Kod*lab postdoc, Aja Mia Carter and Kod*lab robotics researchers, Postdoc Wei-Hsi Chen and PhD student J.Diego Caporale. It’s been two years! Where is her pet T. rex!? [ Kod*Lab ] I am not entirely sure why CMU and HEBI had robots at the 2026 NFL Draft, but I’m entirely sure that it made it more interesting to watch. [ HEBI Robotics ] Thanks, Trevor! Ethan Lauer, a software engineer, answers your questions about robot perception , world modeling, and what spooks our Stretch robot. [ Boston Dynamics ] Yet another thing that a robot is consistently better at than I am. [ Generalist ] If you’re wondering where all those reported humanoid robot sales are coming from, it’s because every big company needs one or two for this sort of thing. [ Impress ] Full color laser yo-yo zapper, a phrase never before written in the history of the universe. [ Ishikawa Group Laboratory ] The future of the L’Oréal Pro 2026 Le Hair Show is... a bald robot? [ LimX Dynamics ] Meet MagicHand H01, our all-new dexterous hand. [ MagicLab ] This is briefly one of the flattest quadrupeds I have ever seen. [ DEEP Robotics ] I appreciate that Engineered Arts did not try to cover up the sound in this video. [ Engineered Arts ] This is very impressive considering that magnets are basically indistinguishable from magic. [ Sung Lab ] NASA has two rovers on Mars—but they’re exploring entirely different eras of the planet’s past. Separated by 2,300 miles, the two rovers are uncovering clues from very different moments in Martian history. Perseverance is on the rim of Jezero Crater, where it’s studying some of the oldest Martian terrain ever explored while searching for signs of ancient microbial life. Meanwhile, Curiosity is climbing Mount Sharp inside Gale Crater, where layers of rock reveal how Mars’ climate changed as water dried up from its surface. [ NASA ] We’ve built a surgical robot to automate key steps in the process of receiving a Neuralink implant to promote safety, reliability, and scalability. [ Neuralink ] The Chinese-made Unitree G1 humanoid robots are making their way into the U.S. And they aren’t just in viral videos but in major tech companies like OpenAI and Nvidia, and top academic institutions. Most arrive through Robostore, a robotics reseller based on Long Island. I went there to watch them come off the pallet, then brought one to my home to see what it could actually do. Are these the future of home robots? A security risk? A Chinese surveillance system on legs? I got answers—and a broken toe. [ New Things ] How do autonomous robots make decisions when the world is unpredictable? From self-driving cars to drone swarms, autonomous systems must operate under uncertainty—making real-time decisions with incomplete or unreliable data. In this video, Harvard SEAS Prof. Stephanie Gil explains how AI-powered robots coordinate, adapt, and stay safe in complex, real-world environments. [ Harvard University ]

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Video Friday: Who Wins in Robot Versus Pro Ping-Pong Player?

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Enjoy today’s videos! Sony AI’s latest research, published on the cover of Nature, addresses a long-standing challenge in physical AI: Can a high-speed autonomous system master the complex perception and dynamic control required to compete against professional athletes? [ Sony AI ] In this video, we present Ringbot Quad, a novel monocycle robot with four legs that combines wheeled and legged locomotion on a single platform. Ringbot Quad is designed as a unique monocycle mechanism that replaces the traditional drivetrain with four individually actuated driving modules, each integrated with an articulated leg. Ringbot Quad aims to provide versatile and efficient mobility through two distinct locomotion modes. In driving mode, the four legs assist with balance and steering, while in walking mode, they fully support the body for quadruped locomotion. By switching between these modes, Ringbot Quad can navigate diverse terrains and overcome obstacles that are difficult for either wheeled or legged systems alone. [ Kinetic Intelligent Machine Lab ] Humanoid robots have beaten human runners in a Beijing half-marathon, marking a breakthrough in China’s rapidly advancing robotics industry. More than 100 robots competed alongside 12,000 people in the 21-kilometer race, with three crossing the finish line ahead of any human. [ Al Jazeera ] Watch AthenaZero juggle barehanded using on-board sensory feedback only. No motion capture. No funnels. No help adding the third ball. The robot learns to adapt to the uncertainties from contact and the appropriate hand-eye coordination. [ Robotics and AI Institute ] From the look of this, it’s based on data capture from humans. What I want to know is, what this will look like when it’s not based on data capture from humans. [ Unitree ] Looks like Sphero would like to fill that sad gap in educational robotics left by LEGO Mindstorms . [ Sphero ] I am pretty sure that this is not how the shell game is played. [ Generalist ] At this point, real value from robots in warehouses much more commonly comes from systems like these, not humanoids. [ Berkshire Grey ] Scientists at the Max Planck Institute for Intelligent Systems propose a method to measure the efficiency of soft electrostatic actuators, enabling systematic evaluation of electrical-to-mechanical energy conversion. Using Peano-HASEL actuators, they demonstrate efficiencies up to 63.6%, over three times higher than previously reported, and validate the approach across other actuator types, paving the way for more energy-efficient soft electrostatic robotic systems. [ Max Planck Institute ] Already deployed in North America, quadruped robots provide continuous patrol, real-time monitoring, and faster incident detection across residential communities—day and night. Um, thanks, but no thanks. [ DEEP Robotics ] Catching drones with what looks like a UR20 robot arm is a neat trick. [ Skydio ] Overactuated drones performing aerial maneuvers will always look just a little bit wrong to me. [ Paper ] from [ ETH Zurich ] Need a rugged and reliable mobile manipulator? Please consider a not-humanoid. [ Clearpath ] This CMU Robotics Institute talk is from CMU’s Raj Reddy, on “The Future of AI : Doomers vs. Abundance.” The last decade has seen extraordinary advances in AI. The potential arrival of Artificial General Intelligence (AGI) has profound implications for future of our society. We anticipate a world where AI assistants and humanoid-robots will perform most of the tasks requiring human expertise and skill at 10% of current costs. In this paradigm, essential services—including food, housing, energy, education, healthcare, and transportation—will be provided via Universal Basic Services, signaling a historic shift from a society of scarcity to one of abundance. This transformation raises a critical concern: widespread displacement of traditional labor. What is the human role when AI can do everything? This talk presents an alternative scenario: a “Human-in-the-Loop” evolution. In this model, humans transition into high-level supervisory roles, collaborating with AGI to train robots in novel skills and adapt them to unforeseen tasks. We explore this as the “Maharaja Model” where technology serves humanity so comprehensively that work will be optional for humans. Finally, we will discuss how institutions like the Robotics Institute must lead this transition, developing the hybrid technologies and ethical frameworks necessary to bridge the gap between our current economy and a robot-assisted future. [ Carnegie Mellon University Robotics Institute ]

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Video Friday: Digit Learns to Deadlift

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Enjoy today’s videos! Training a policy for Digit to perform a deadlift isn’t just about Digit impressing colleagues–it lets us push the limits of our hardware and training methodologies. The heavier the object (in this case 65 pounds [29.5 kg]) the more whole-body coordination we need in our controller, and the more resilience Digit’s actuators and joints require. By including whatever object we want Digit to lift in simulation as we train a new policy, we’re able to account for load distribution, grip forces, and changes to Digit’s center of mass–the result is a policy that translates to a dynamically balanced lift in the real world. New robot, you say...? [ Agility ] Gatlin Robotics is proud to unveil our first commercial, showcasing our robots in action for our debut Robot-as-a-Service (RaaS) contract! [ Gatlin Robotics ] Thanks, Erika! At Dexterity, we build robots designed for precision, adaptability, and real-world problem solving. But every now and then, we like to remind ourselves (and everyone else) that motion intelligence isn’t just about efficiency—it can be expressive, fluid, even a little playful. [ Dexterity ] Harvard researchers built a swarm of simple ant-like robots (RAnts) that can collectively excavate and construct structures without central control. By tuning just two parameters—cooperation strength and material deposition rate—the same swarm can switch between building new structures and dismantling existing ones. Adaptive group behavior can emerge from the interaction between many simple agents and their environment, with potential applications in many fields. [ Harvard University ] I really appreciate companies who give their robots the ability to entertain themselves . [ Generalist ] “Spark of Color.” Manvi Saxena, Yihao Geng, Jason Brown, Daniel Newman, Cameron Aubin. A tiny controlled explosion inflates the soft membrane of a microcombustion actuator, sending colorful, carefully arranged water droplets skyward. The actuator measures just 8 mm in diameter, while the high-speed sequence captures only 3 milliseconds of motion. The work challenges the assumption that soft actuators must be slow or gentle, showing instead how softness can also be fast, forceful, and explosive. [ Michigan Robotics ] With the physique of an ordinary person, running at a world champion’s speed! I am questioning whether it knows how to stop. [ Unitree Robotics ] Aww [ Boston Dynamics ] In this episode of Innovator Story, the FotoBot team from The University of Hong Kong made an appearance and conducted on-site tests with their AI photography robot at Shenzhen Bay Talent Park. Relying on TRON 1, it easily handles complex terrains such as grasslands, slopes, and stairs, unlocking a brand-new “Robot + Photography” experience for the public. [ LimX Dynamics ] The objective of this game is to cover up as much of the hole as possible, right? [ Kinetic Intelligent Machine Lab ] MagicLab Robotics just deployed a massive swarm of robot dogs and humanoids at the Jiangsu Super League opening ceremony. Beyond a stunning spectacle, this is live proof of Embodied AI at scale. Coordinating a cross-category fleet in a complex, open-air environment proves our multi-agent control systems are ready for real-world deployment. [ MagicLab ] A swarm of drones being launched out of the back of a Chinook would be terrifying except that from this angle, it looks like the drones are being puked out by an astonished frog. [ Boeing ] Welcome to Robot Talk, from IHMC Robotics! [ IHMC Robotics ] Third-year ‪Michigan Engineering‬ undergrad Yulei Fu sits down with Professor Jessy Grizzle to talk about what it’s actually like to major in Robotics at ‪University of Michigan. What makes it different from CS or ME? Where do graduates end up? Are the courses brutal? And what makes the department feel like a community instead of a competition? [ Michigan Robotics ] This CMU RI Yata Memorial Lecture is by Boris Softman, on “Journeys from Research to Commercialization: Lessons from Anki, Waymo, and Bedrock Robotics.” In this lecture, Boris will share an honest account of that journey and its lessons, including the energizing wins, the wrong turns and painful surprises, and the moments where an earlier experience turned out to matter more than expected. Closing with a deeper look at Bedrock, he will share why he believes autonomous construction is one of the most important problems robotics can tackle right now, driven by a unique convergence of maturing technology and critical industry need. For students at the beginning of their own paths, this is a talk about how a career in robotics and entrepreneurship might actually unfold, the many variables one navigates in the journey, and why the connections you cannot yet see may end up being the most valuable ones. [ Carnegie Mellon University Robotics Institute ]

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​Boston Dynamics and Google DeepMind Teach Spot to Reason​

The amazing and frustrating thing about robots is that they can do almost anything you want them to do, as long as you know how to ask properly. In the not-so-distant past, asking properly meant writing code, and while we’ve thankfully moved beyond that brittle constraint, there’s still an irritatingly inverse correlation between ease of use and complexity of task. AI has promised to change that. The idea is that when AI is embodied within robots—giving AI software a physical presence in the world—those robots will be imbued with with reasoning and understanding. This is cutting-edge stuff, though, and while we’ve seen plenty of examples of embodied AI in a research context, finding applications where reasoning robots can provide reliable commercial value has not been easy. Boston Dynamics is one of the few companies to commercially deploy legged robots at any appreciable scale; there are now several thousand hard at work. Today the company is announcing that its quadruped robot Spot is now equipped with Google DeepMind’s Gemini Robotics-ER 1.6 , a high-level embodied reasoning model that brings usability and intelligence to complex tasks. YouTube.com Although this video shows Spot in a home context, the focus of this partnership is on one of the very few applications where legged robots have proven themselves to be commercially viable: inspection. That is, wandering around industrial facilities, checking to make sure that nothing is imminently exploding. With the new AI onboard, Spot is now able to autonomously look for dangerous debris or spills, read complex gauges and sight glasses, and call on tools like vision-language-action models when it needs help understanding what’s going on in the environment around it. “Advances like Gemini Robotics ER 1.6 mark an important step toward robots that can better understand and operate in the physical world,” Marco da Silva , Vice President and General Manager of Spot at Boston Dynamics, says in a press release . “Capabilities like instrument reading and more reliable task reasoning will enable Spot to see, understand, and react to real-world challenges completely autonomously.” Understanding Robot Understanding The words “reasoning” and “understanding” are being increasingly applied to AI and robotics, but as Toyota Research Institute’s Gill Pratt recently pointed out , what those words actually mean for robots in practice isn’t always clear. “The benchmark we measure ourselves against when it comes to understanding is that the system should answer the way a human would,” Carolina Parada , Head of Robotics at Google DeepMind, explained in an interview. For robots to reliably and safely perform tasks, this connection between how robots understand the world and how humans do is critical. Otherwise, there may be a disconnect between the instructions that a human gives a robot, and how the robot decides to carry out that task. Boston Dynamics’ video above is a potentially messy example of this. One of the instructions to Spot was to “recycle any cans in the living room.” It has no problem completing the task, as the video shows, but in doing so it grips the can sideways, which is not going to end up well for cans that have leftover liquid in them. We humans would avoid this because we can draw on a lifetime of experience to know how cans should be held, but robots don’t (yet) have that kind of world knowledge. Parada says that Gemini Robotics-ER 1.6 approaches situations like this from a safety perspective. “If you ask the robot to bring you a cup of water, it will reason not to place it on the edge of a table where it could fall. We track this using our ASIMOV benchmark , which includes a whole lot of natural language examples of things the robot should not do.” The current version of Spot doesn’t use these semantic safety models for manipulation, but the plan is to make future versions reason about holding objects in ways that are safe. YouTube.com There does still seem to be a disconnect between Gemini Robotics-ER 1.6 as a high-level reasoning model for a robot, and the robot itself as an interface with the physical world. One of the new features of 1.6 is success detection , which combines multiple camera angles to more reliably be able to tell when Spot has successfully grasped an object. This is great if you’re relying entirely on vision for your object interaction, but robots have all kinds of other well-established ways to detect a successful grasp, including touch sensors and force sensors, that 1.6 is not using. The reason why this is the case speaks to a fundamental problem that the robotics field is still trying to figure out: how to train models when you need physical data. “At the moment, these models are strictly vision only,” Parada explains. “There is lots of [visual] information on the web about how to pick up a pen. If we had enough data with touch information, we could easily learn it, but there is not a lot of data with touch sensing on the internet.” Customers who use these new capabilities for inspection with Spot will be required to share their data with Boston Dynamics, which is where some of this data will come from. Real-World Robots That Are Useful The fact that Boston Dynamics has customers makes them something of an anomaly when it comes to legged robots that rely on AI in commercial deployments. And those customers will have to be able to trust the robot—always a problem when AI is involved . “We take this very seriously,” da Silva said in an interview. “We roll out new DeepMind capabilities through beta programs to a smaller set of customers to understand what to anticipate, and we only actively advertise features we are confident will work.” There’s a threshold of usefulness that robots like Spot need to reach, and fortunately, the real world doesn’t demand perfection. “Most critical infrastructure in a facility will be instrumented to tell you whether something is wrong,” da Silva says. “But there is a lot of stuff that is not instrumented that can still cause a problem if you aren’t paying attention to it. We’ve found that somewhere north of 80 percent is the threshold where it’s not annoying. Below that, basically the robot is crying wolf, and the operators will start ignoring it.” Both da Silva and Parada agree that there’s still plenty of room for improvement in robotic inspection. As Parada points out, Spot’s rarefied status as a scalable commercial platform provides a valuable opportunity to learn how models like Gemini Robotics-ER 1.6 can be the most useful, and then apply that knowledge to other embodied AI platforms, including Boston Dynamics’ Atlas . Does that mean that Atlas is going to be the next industrial inspection robot? Probably not. But if this real-world experience can get us closer to safe and reliable robots that can pick up laundry, take a dog for a walk, and clear away soda cans without making a mess, that’s something we can all get excited about.

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Video Friday: This Floor Lamp Will Do Your Chores

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Enjoy today’s videos! Lume is a sculptural floor lamp designed to feel at home the moment you place it. It’s crafted from anodized aluminum and high-gloss finishes, shaped into a slender, balanced form that quietly conceals its complexity. Every surface is refined to feel smooth, precise, and enduring. When it moves, it’s quiet and deliberate. When it’s still, it holds its place with ease. Apparently, and let me stress that ‘apparently,’ Lume can make the bed, fold laundry , and do other chores involving soft materials. I’m intensely skeptical because it feels like that video has more footage of people staring out of windows and dancing for no reason beyond the robot actually doing anything. And when you do see the robot working at a task, it’s cut up into lots of different pieces of footage in a way that is typically used to distract from either plodding speed, frequent failures, or both. So, yeah. There may be a lot to like about the philosophy here, but even at a suspiciously cheap US$2,500 for a pair of these robots, more detail is certainly called for before they’ve earned your preorder. [ Syncere ] In Science Robotics, researchers from MIT Media Lab and collaborators from Politecnico di Bari present Electrofluidic Fiber Muscles, a new class of artificial muscle fibers for robots and wearables. Unlike the rigid servo motors used in most robots, these fiber-shaped muscles are soft and flexible. They combine electrohydrodynamic (EHD) fiber pumps—slender tubes that move liquid using electric fields to generate pressure with no moving parts—with fluidic fiber actuators. The muscles are driven by electric fields and operate silently, with no external pumps or reservoirs. [ MIT ] We first saw this thing at ICRA@40 a few years ago, but the paper is out now. [ Nature Communications ] via [ LASA ] I do like tea, and I suppose there could be worse applications for a robot than this one, since it leverages both payload and complex terrain mobility. [ DEEP Robotics ] We’ve created GEN-1, our latest milestone in scaling robot learning. We believe it to be the first general-purpose AI model that crosses a new performance threshold: mastery of simple physical tasks. It improves average success rates to 99% on tasks where previous models achieve 64%, completes tasks roughly 3x faster than state of the art, and requires only 1 hour of robot data for each of these results. GEN-1 unlocks commercial viability across a broad range of applications—and while it cannot solve all tasks today, it is a significant step towards our mission of creating generalist intelligence for the physical world. [ Generalist ] Legged manipulators offer high mobility and versatile manipulation. However, robust interaction with heterogeneous articulated objects, such as doors, drawers, and cabinets, remains challenging because of the diverse articulation types of the objects and the complex dynamics of the legged robot. In this paper, we propose a robust and sample-efficient framework for opening heterogeneous articulated objects with a legged manipulator. [ OpenHEART ] By deeply coupling real-time depth perception with reinforcement learning motion control, Adam achieves natural human-like stair-stepping gait, showing outstanding dynamic stability and environmental adaptability. [ PNDbotics ] The way these robots deliver packages will never not be amusing to me. [ DEEP Robotics ] Tether performs autonomous real-world functional play involving structured, task-directed interactions. We introduce a policy that performs trajectory warping anchored by keypoint correspondences, which is extremely data efficient and robust to significant spatial and semantic environment variation. Running the policy within a VLM-guided multi-task loop, we generate a stream of play data that consistently improves downstream policy learning over time. [ Tether ] What happens when your walls begin to move? This paper explores the design of human-robot interaction for architectural-scale, shape-changing environments. [ Interactive Structures Lab ] I will admit to being somewhat disappointed about the reality of the Unreal Robotics Lab. [ URLab ] We’re not done yet! Illinois is back in the Final Four for the first time since 2005, and we’re cheering all the way to the championship. This video features teleoperated G1 and AI Worker robots. [ KIMLAB ] Fighting robots are cool. Destroying expensive electronics while fighting robots is not cool. We make robots out of plastic so our electronics survive. [ Weaponized Plastic Fighting League ]

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Video Friday: Digit Learns to Dance—Virtually Overnight

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Enjoy today’s videos! Getting Digit to dance takes more than putting on some fancy shoes–our AI Team can teach Digit new whole-body control capabilities overnight. Using raw motion data from mocap, animation, and teleop methods, Digit gets new skills through sim-to-real reinforcement training. [ Agility ] We’ve created GEN-1, our latest milestone in scaling robot learning. We believe it to be the first general-purpose AI model that crosses a new performance threshold: mastery of simple physical tasks. It improves average success rates to 99% on tasks where previous models achieve 64%, completes tasks roughly 3x faster than state of the art, and requires only 1 hour of robot data for each of these results. GEN-1 unlocks commercial viability across a broad range of applications—and while it cannot solve all tasks today, it is a significant step towards our mission of creating generalist intelligence for the physical world. [ Generalist ] Unitree open-sources UnifoLM-WBT-Dataset—high-quality real-world humanoid robot whole-body teleoperation (WBT) dataset for open environments. Publicly available since March 5, 2026, the dataset will continue to receive high-frequency rolling updates. It aims to establish the most comprehensive real-world humanoid robot dataset in terms of scenario coverage, task complexity, and manipulation diversity. [ Hugging Face ] Autonomous mobile robots operating in human-shared indoor environments often require paths that reflect human spatial intentions, such as avoiding interference with pedestrian flow or maintaining comfortable clearance. This paper presents MRReP, a Mixed Reality-based interface that enables users to draw a Hand-drawn Reference Path (HRP) directly on the physical floor using hand gestures. [ MRReP ] Thanks, Masato! Eye contact, even momentarily between strangers, plays a pivotal role in fostering human connection, promoting happiness, and enhancing belonging. Through autonomous navigation and adaptive mirror control, Mirrorbot facilitates serendipitous, non-verbal interactions by dynamically transitioning reflections from self-focused to mutual recognition, sparking eye contact, shared awareness, and playful engagement. [ ARL ] via [ Cornell University ] Experience PAL Robotics’ new teleoperation system for TIAGo Pro, the AI-ready mobile manipulator designed for advanced research. This real-time VR teleoperation setup allows precise control of TIAGo Pro’s dual arms in Cartesian space, ideal for remote manipulation, AI data collection, and robot learning. [ PAL Robotics ] Utter brilliance from Robust AI. No notes. [ Robust AI ] Come along with our Senior Test Engineer, Nick L., as he takes us on a tour of the Home Test Labs inside the iRobot HQ. [ iRobot ] By automating the final “magic 5%” of production—the precise trimming of swim goggles’ silicone gaskets based on individual face scans—UR cobots allow THEMAGIC5 to deliver affordable, custom-fit goggles, enabling the company to scale from a Kickstarter sensation to selling over 400,000 goggles worldwide. [ Universal Robots ] Sanctuary AI has once again demonstrated its industry-leading approach to training dexterous manipulation policies for its advanced hydraulic hands. In this video, their proprietary hydraulic hand autonomously manipulates a lettered cube, continuously reorienting it to match a specified goal (displayed in the bottom-left corner of the video). [ Sanctuary AI ] China’s Yuxing 3-06 commercial experimental satellite, the first of its kind to be equipped with a flexible robotic arm, has recently completed an in-orbit refueling test and verification of key technologies. The test paves the way for Yuxing 3-06, dubbed a “space refueling station,” to refuel other satellites in orbit, manage space debris, and provide other in-orbit services. [ Sanyuan Aerospace ] via [ Space News ] This is a demonstration of natural walking, whole-body teleoperation, and motion tracking with our custom-built humanoid robot. The control policies are trained using large-scale parallel reinforcement learning (RL). By deploying robust policies learned in a physics simulator onto the real hardware, we achieve dynamic and stable whole-body motions. [ Tokyo Robotics ] Faced with aging railway infrastructure, a shrinking workforce and rising construction costs, Japan Railway West asked construction innovator Serendix to replace an old wooden building at its Hatsushima railway station using its 3D printing technology. An ABB robot enabled the company to assemble the new building in a single night ready for the first train service the next day. [ ABB ] Humanoid, SAP, and Martur Fompak team up to test humanoid robots in automotive manufacturing logistics. This joint proof of concept explores how robots can streamline operations, improve efficiency, and shape the future of smart factories. [ Humanoid ] This MIT Robotics Seminar is from Dario Floreano at EPFL, on “Avian Inspired Drones.” [ MIT ] This MIT Robotics Seminar is from Ken Goldberg at UC Berkeley, on “Good Old-Fashioned Engineering Can Close the 100,000 Year “Data Gap” in Robotics.” [ MIT ]

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Gill Pratt Says Humanoid Robots’ Moment Is Finally Here

In 2012, the U.S. Defense Advanced Research Projects Agency announced the DARPA Robotics Challenge (DRC). The multi-year, multi-million-dollar competition for disaster robotics resulted in Boston Dynamics’ Atlas , some absolutely incredible moments from one of the very first generations of useful humanoid robots, and a blooper video that will live on forever. Gill Pratt , the architect of the competition, had a very clear understanding of what the DRC was going to do for robotics. “The reason [for the DARPA Robotics Challenge] is actually to push the field forward and make this capability a reality,” Pratt told IEEE Spectrum in 2012 . At the time, he pointed out that before the DARPA Grand Challenge in 2004 and the DARPA Urban Challenge in 2007, driverless cars for complex environments essentially did not exist. He saw the DRC doing the same thing for robotics. It’s been about a decade since the conclusion of the DARPA Robotics Challenge , and many in the industry believe humanoid robots are about to have the transformative moment that Pratt predicted. But as is common in robotics, things tend to be far more difficult than it seems like they should be. Spectrum checked in with Pratt, now the CEO of the Toyota Research Institute (TRI), to find out what’s holding humanoid robotics back, what he thinks these robots should be doing (or not doing), and how to navigate the humanoid hype bubble. What do you think about this robotics moment that we’re in? Gill Pratt: What has changed is actually not about humanoids. Many people have been building research robots in the humanoid form for a long time. What’s different now isn’t the body, but the brain. We have always had this disparity in the robotics field where the mechanisms we were building were incredibly capable, but we didn’t really have the means for making the utility of the robot match that potential. Now we actually do, and that’s because of the AI revolution that has happened over the last few years. It’s very tempting to look back ten years and directly credit the DRC with a lot of what is now happening with commercial humanoids. Is there any reason not to do that? Gill Pratt poses with an early version of NASA’s Valkyrie DRC robot. Gill Pratt Pratt: No, but I want to be humble about it. The DRC was focused on half autonomy and half teleoperation in real time. There was remote supervision, and then semi-autonomy to amplify that supervision to handle tasks in real-time while the remote person was telling the robot what to do. That was all before the breakthroughs that have happened in AI recently. What has changed now is that we have a way to essentially teach robots what to do, and make them competent in a way that doesn’t require writing code; you can just demonstrate the task to the robot instead. With a sufficient amount of that data and new AI methods, robots can be far more performant than ever before. But that data is a bottleneck, right? How do we know what it should consist of, and what a sufficient amount is to get a robot to do something reliably? Pratt: This mirrors exactly the debate going on in large language models [LLMs]. You have certain people who believe that if you take LLMs—which are auto-regressive predictors that guess what the next word should be based on past words—and patch them up with a variety of methods to solve their hallucinations, we’ll eventually get to a point where we can trust the AI system. And then there are other people, and I think Yann LeCun is the most well-known of them, who say that’s nonsense, and we need something else. His view, and I agree, is that we need world models. We need some way for the AI system to imagine, try things out, and truly reason. And I know that we’re applying words like ‘reason’ to what are essentially pattern-matching systems. Saying that there’s ‘reasoning’ is just a sticker we put on whatever we’ve built; it’s not true reasoning. Data Bottlenecks in Robot Learning This is an example of ”system one” versus “system two” thinking, right? Pratt: Yes. System one is the fast, reflexive thinking we have, which is the kind of pattern matching that current LLMs do. System two is the slow reasoning that involves imagination and world models. That’s what we have not done yet. Progress on system one has been extraordinary, but we still don’t have system two. These attempts to patch system one to make it system two are like trying to squeeze a balloon filled with water; you squeeze it on one side and the water bulges out on the other side. You keep getting surprised that you fix one thing and something else breaks, and the performance overall doesn’t really get that much better. How have you been approaching this problem at TRI? Pratt: Two years ago, we came up with diffusion policy , and then we came up with what I call large behavior models (LBMs). That involves having one model trained on many tasks, and showing that as you add each task, it actually helps with the other tasks and cuts down on the amount of training data needed to reach a given level of performance. These have been incredible system one advances. The breakthrough happened when we realized that diffusion could be applied to robot behavior. We discovered that operating in the behavior space, from vision in, to action out, worked incredibly well. That kicked off the whole field, and since then, I think every robotics demonstration that we’ve seen is using some form of diffusion policy to do what it’s doing. But again, this is system one pattern matching: ‘If I see the world like this, I act on the world like that.’ The robot’s not imagining, thinking, and planning the way traditional robotics with hand coding used to do. It’s just reacting. System one’s pattern matching often breaks down in the real world, though, as we’ve seen with autonomous driving’s struggles. Pratt: Ten years ago, when TRI first started, almost everybody was saying that automated driving was right around the corner. Ten years later, I do think we are now there, and the remaining questions are business ones: How much does the hardware cost, the insurance, the support, does it economically make sense? We haven’t necessarily solved automated driving, but our solutions are good enough, because we use humans for backup. When an automated vehicle gets stuck at a double-parked car, it calls home and asks a person for a system two decision. I think other robots could do that also. Most of the time they do their work on their own, and every once in a while, they raise their hand for help. If we’ve just barely managed to get autonomous cars right, why are we devoting so much attention to the legged humanoid form factor? Pratt: We’ve built the world with physical affordances for our bodies. If the robot is to do well in that world, it should have something that takes advantage of those affordances. It’s also easier for imitation learning to work because we have the same form. And legs are good for certain environments; you can step over obstacles to balance faster than you can roll to a new point of support with wheels. Having said all that, legs are not always the most practical thing. It’s very weird to see so much focus on legged robots in factories, which are flat environments perfectly suited for wheels. Managing the Humanoid Robotics Hype Do you think that the amount of money being poured into legged humanoids is a good thing for robotics? Pratt: It has both advantages and dangers. It’s wonderful seeing so many resources into the robotics field, and I do think that something special has occurred. Things are not the way they were before, and there are so many possibilities when you think about people teaching robots how to do things. Gill Pratt admires a robot on the roof of the Ghibli Museum in Tokyo. Gill Pratt What kinds of things should humans be teaching robots to do? Pratt: For ten years at TRI, we’ve been thinking about society and aging . It’s not just about physical disability; it’s about loneliness and loss of purpose, which are far more prevalent (and far worse) problems. And so the question is, what can we do technologically to help people feel that they’re younger? At TRI, we’re exploring “care-receiving robots”—robots that receive teaching from a human. We have evolved to be creatures that love giving and love helping. When you program a machine by demonstration, and that machine goes on to help someone else, you feel a sense of purpose. We think robots can be bi-directional things to improve quality of life psychologically, not only physically. When you started TRI ten years ago, I asked you what you would be focusing on, your answer really stuck with me: you said elder care, because ‘we don’t have a choice.’ Pratt: Yes. The statistics in Japan and the U.S. are only getting worse, and we don’t have a choice. It’s important to remember that an aging society has a huge impact on young people. This is because of the dependency ratio, which is how many young people in the workforce are supporting both people that are too young to work, and also people that are too old to work. Those numbers keep getting worse and worse. How do we solve this? Pratt: We’ve had some incredible breakthroughs with system one, but it doesn’t mean the robots are going to be doing all that much, unless somebody makes a system two breakthrough also. Or, where we have a system where humans provide some level of system two supervisory control. That kind of human supervisory control takes us right back to the DRC, doesn’t it? Pratt: [Laughs] That’s exactly right! Look, I’m not going to tell you not to praise the DRC… There was someone who called it the ‘Woodstock of Robots ,’ which just warmed my heart, that was so cool! So, ten years later, how do you feel about the amount of hype in humanoid robotics right now? Pratt: We are approaching what (I hope!) is a peak of inflated expectations for humanoids. And that’s because nobody’s thinking deeply enough about the system one versus system two thing. Right now, our physical AI systems are just pattern matching. They’re incredibly capable, and it’s astonishing how good these things are—we are so proud of it. And we do believe that aggregating learning from many tasks through large behavior models will be incredibly effective. But it’s still not system two. There’s a lot of overpromising going on, and it’s very sad because it’s setting us up for a fall. What I’m worried about is the trough of disillusionment that will follow. How do we avoid that crash in robotics when the humanoid hype bubble bursts? Pratt: For now, we need damping. In control systems, you stabilize an unstable system by adding damping. The press and the academic world can add lead compensation by reminding everyone that what we’re seeing in humanoids now isn’t really reasoning. We should also remember that the automated driving field went through a bubble burst also, and just a few companies survived that by keeping the hype down and being persistent. I think we should do that here, too.

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Video Friday: Beep! Beep! Roadrunner Bipedal Bot Breaks the Mold

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Enjoy today’s videos! “Roadrunner” is a new bipedal wheeled robot prototype designed for multi-modal locomotion. It weighs around 15 kg (33 lb) and can seamlessly switch between its side-by-side and in-line wheel modes and stepping configurations depending on what is required for navigating its environment. The robot’s legs are entirely symmetric, allowing it to point its knees forward or backward, which can be used to avoid obstacles or manage specific movements. A single control policy was trained to handle both side-by-side and in-line driving. Several behaviors, including standing up from various ground configurations and balancing on one wheel, were successfully deployed zero-shot on the hardware. [ Robotics and AI Institute ] Incredibly (INCREDIBLY!) NASA says that this is actually happening. NASA’s SkyFall mission will build on the success of the Ingenuity Mars helicopter, which achieved the first powered, controlled flight on another planet. Using a daring mid-air deployment, SkyFall will deliver a team of next-gen Mars helicopters to scout human landing sites and map subsurface water ice. [ NASA ] NASA’s MoonFall mission will blaze a path for future Artemis missions by sending four highly mobile drones to survey the lunar surface around the Moon’s South Pole ahead of astronauts’ arrival there. MoonFall is built on the legacy of NASA’s Ingenuity Mars Helicopter. The drones will be launched together and released during descent to the surface. They will land and operate independently over the course of a lunar day (14 Earth days) and will be able to explore hard-to-reach areas, including permanently shadowed regions (PSRs), surveying terrain with high-definition optical cameras and other potential instruments. For what it’s worth, Moon landings have a success rate well under 50%. So let’s send some robots there to land over and over! [ NASA ] In Science Robotics, researchers from the Tangible Media group led by Professor Hiroshi Ishii, together with colleagues from Politecnico di Bari, present Electrofluidic Fiber Muscles: a new class of artificial muscle fibers for robots and wearables. Unlike the rigid servo motors used in most robots, these fiber-shaped muscles are soft and flexible. They combine electrohydrodynamic (EHD) fiber pumps — slender tubes that move liquid using electric fields to generate pressure silently, with no moving parts — with fluid-filled fiber actuators. These artificial muscles could enable more agile untethered robots, as well as wearable assistive systems with compact actuation integrated directly into textiles. [ MIT Media Lab ] In this study, we developed MEVIUS2, an open-source quadruped robot. It is comparable in size to Boston Dynamics Spot, equipped with two LiDARs and a C1 camera, and can freely climb stairs and steep slopes! All hardware, software, and learning environments are released as open source. [ MEVIUS2 ] Thanks, Kento! What goes into preparing for a live performance? Arun highlights the reliability testing that goes into trying a new behavior for Spot. [ Boston Dynamics ] In this work, a multi-robot planning and control framework is presented and demonstrated with a team of 40 indoor robots, including both ground and aerial robots. That soundtrack though. [ GitHub ] Thanks, Keisuke! Quadrupedal robots can navigate cluttered environments like their animal counterparts, but their floating-base configuration makes them vulnerable to real-world uncertainties. Controllers that rely only on proprioception (body sensing) must physically collide with obstacles to detect them. Those that add exteroception (vision) need precisely modeled terrain maps that are hard to maintain in the wild. DreamWaQ++ bridges this gap by fusing both modalities through a resilient multi-modal reinforcement learning framework. The result: a single controller that handles rough terrains, steep slopes, and high-rise stairs—while gracefully recovering from sensor failures and situations it has never seen before. That cliff behavior is slightly uncanny. [ DreamWaQ++ ] I take issue with this from iRobot: While the pyramid exploration that iRobot did was very cool, they did it with a custom made robot designed for a very specific environment. Cleaning your floors is way, way harder. Here’s a bit more detail on the pyramids thing: [ iRobot ] More robots in circus please! [ Daniel Simu ] MIT engineers have designed a wristband that lets wearers control a robotic hand with their own movements. By moving their hands and fingers, users can direct a robot to perform specific tasks, or they can manipulate objects in a virtual environment with high-dexterity control. [ MIT ] At NVIDIA GTC 2026 , we showcased how AI is moving into the physical world. Visitors interacted with robots using voice commands, watching them interpret intent and act in real time — powered by our KinetIQ AI brain. [ Humanoid ] Props to Sony for their continued support and updates for Aibo ! [ Aibo ] This robot looks like it could be a little curvier than normal? [ LimX Dynamics ] Developed by Zhejiang Humanoid Robot Innovation Center Co., Ltd., the Naviai Robot is an intelligent cooking device. It can autonomously process ingredients, perform cooking tasks with high accuracy, adjust smart kitchen equipment in real time, and complete post-cooking cleaning. Equipped with multi-modal perception technology, it adapts to daily kitchen environments and ensures safe and stable operation. That 7x is doing some heavy lifting. [ Zhejiang Lab ] This CMU RI Seminar is by Hadas Kress-Gazit from Cornell, on “Formal Methods for Robotics in the Age of Big Data.” Formal methods – mathematical techniques for describing systems, capturing requirements, and providing guarantees – have been used to synthesize robot control from high-level specification, and to verify robot behavior. Given the recent advances in robot learning and data-driven models, what role can, and should, formal methods play in advancing robotics? In this talk I will give a few examples for what we can do with formal methods, discuss their promise and challenges, and describe the synergies I see with data-driven approaches. [ Carnegie Mellon University Robotics Institute ]

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Video Friday: Humanoid Learns Tennis Skills Playing Humans

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Enjoy today’s videos! Human athletes demonstrate versatile and highly dynamic tennis skills to successfully conduct competitive rallies with a high-speed tennis ball. However, reproducing such behaviors on humanoid robots is difficult, partially due to the lack of perfect humanoid action data or human kinematic motion data in tennis scenarios as reference. In this work, we propose LATENT, a system that Learns Athletic humanoid TEnnis skills from imperfect human motioN daTa. [ LATENT ] A beautifully designed robot inspired by Strandbeests. [ Cranfield University ] We believe we’re the first robotics company to demonstrate a robot peeling an apple with dual dexterous human-like hands. This breakthrough closes a key gap in robotics, achieving bimanual, contact-rich manipulation and moving far beyond the limits of simple grippers. Today’s AI models (VLMs) are excellent at perception but struggle with action. Controlling high-degree-of-freedom hands for tasks like this is incredibly complex, and precise finger-level teleoperation is nearly impossible for humans. Our first step was a shared-autonomy system: rather than controlling every finger, the operator triggers pre-learned skills like a “rotate apple or tennis ball” primitive via a keyboard press or pedal. This makes scalable data collection and RL training possible. How does the AI manage this? We created “MoDE-VLA ” (Mixture of Dexterous Experts). It fuses vision, language, force, and touch data by using a team of specialist “experts,” making control in high-dimensional spaces stable and effective. The combination of these two innovations allows for seamless, contact-rich manipulation. The human provides high-level guidance, and the robot executes the complex in-hand coordination required. [ Sharpa ] Thanks, Alex! It was great to see our name amongst the other “AI Native” companies during the NVIDIA GTC keynote. NVIDIA Isaac Lab helps us train reinforcement learning policies that enable the UMV to drive, jump, flip, and hop like a pro. [ Robotics and AI Institute ] This Finger-Tip Changer technology was jointly researched and developed through a collaboration between Tesollo and RoCogMan LaB at Hanyang University ERICA. The project integrates Tesollo’s practical robotic hand development experience with the lab’s expertise in robotic manipulation and gripper design. I don’t know why more robots don’t do this. Also, those pointy fingertips are terrifying. [ RoCogMan LaB ] Here’s an upcoming ICRA paper from the Fluent Robotics Lab at the University of Michigan featuring an operational PR2 ! With functional batteries!!! [ Fluent Robotics Lab ] This video showcases the field tests and interaction capabilities of KAIST Humanoid v0.7, developed at the DRCD Lab featuring in-house actuators. The control policy was trained through deep reinforcement learning leveraging human demonstrations. [ KAIST DRCD Lab ] This needs to come in adult size. [ DEEP Robotics ] I did not know this, but apparently shoeboxes are really annoying to manipulate because if you grab them by the lid, they just open, so specialized hardware is required. [ Nomagic ] Thanks, Gilmarie! This paper presents a method to recover quadrotor Unmanned Air Vehicles (UAVs) from a throw, when no control parameters are known before the throw. [ MAVLab ] Uh oh, robots can see glass doors now. We’re in trouble. [ LimX Dynamics ] This drone hugs trees [ Stanford BDML ] Electronic waste is one of the fastest-growing environmental problems in the world. As robotics and electronic systems become more widespread, their environmental footprint continues to increase. In this research, scientists developed a fully biodegradable soft robotic system that integrates electronic devices, sensors, and actuators, yet completely decomposes after use. [ Nature ] We developed a distributed algorithm that enables multiple aerial robots to flock together safely in complex environments, without explicit communication or prior knowledge of the surroundings, using only on-board sensors and computation. Our approach ensures collision avoidance, maintains proximity between robots, and handles uncertainties (tracking errors and sensor noise). Tested in simulations and real-world experiments with up to four drones in a dense forest, it proved robust and reliable. [ RBL ] The University of Pennsylvania’s 2025 President’s Sustainability Prize winner Piotr Lazarek has developed a system that uses satellite data to pinpoint inefficiencies in farmers’ fields, conducts real-time soil analysis with autonomous drones to understand why they occur, and generates precise fertilizer application maps. His startup Nirby aims to increase productivity in farm areas that are underperforming and reduce fertilizer in high-performing ones. [ University of Pennsylvania ] The production version of Atlas is a departure from the typical humanoid form factor, favoring industrial utility over human likeness. Intended for purposeful work in an industrial setting, Atlas has a form factor that signals its role as a machine rather than a companion or friendly assistant. Join two lead hardware engineers and our head of industrial design for a technical discussion of how key product requirements, ranging from passive thermal management to a modular architecture, dictated a bold new vision for a humanoid. [ Boston Dynamics ] Dr. Christian Hubicki gives a talk exploring the common themes of modern robotics research and his time on the reality competition show, Survivor. [ Optimal Robotics Lab ]

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Video Friday: These Robots Were Born to Run

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA Enjoy today’s videos! All legged robots deployed “in the wild” to date were given a body plan that was predefined by human designers and could not be redefined in situ. The manual and permanent nature of this process has resulted in very few species of agile terrestrial robots beyond familiar four-limbed forms. Here, we introduce highly athletic modular building blocks and show how they enable the automatic design and rapid assembly of novel agile robots that can “hit the ground running” in unstructured outdoor environments. [ Northwestern UniversityCenter for Robotics and Biosystems ] [ Paper ] via [ Gizmodo ] If you were going to develop the ideal urban delivery robot more or less from scratch, it would be this. [ RIVR ] Don’t get me wrong, there are some clever things going on here, but I’m still having a lot of trouble seeing where the unique, sustainable value is for a humanoid robot performing these sorts of tasks. [ Figure ] One of those things that you don’t really think about as a human, but is actually pretty important. [ Paper ] via [ ETH Zurich ] We propose TRIP-Bag (Teleoperation, Recording, Intelligence in a Portable Bag), a portable, puppeteer-style teleoperation system fully contained within a commercial suitcase, as a practical solution for collecting high-fidelity manipulation data across varied settings. [ KIMLAB ] We propose an open-vocabulary semantic exploration system that enables robots to maintain consistent maps and efficiently locate (unseen) objects in semi-static real-world environments using LLM-guided reasoning. [ TUM ] That’s it folks, we have no need for real pandas anymore—if we ever did in the first place. Be honest, what has a panda done for you lately? [ MagicLab ] RoboGuard is a general-purpose guardrail for ensuring the safety of LLM-enabled robots. RoboGuard is configured offline with high-level safety rules and a robot description, reasons about how these safety rules are best applied in robot’s context, then synthesizes a plan that maximally follows user preferences while ensuring safety. [ RoboGuard ] In this demonstration, a small team responds to a (simulated) radiation contamination leak at a real nuclear reactor facility. The team deploys their reconfigurable robot to accompany them through the facility. As the station is suddenly plunged into darkness, the robot’s camera is hot-swapped to thermal so that it can continue on. Upon reaching the approximate location of the contamination, the team installs a Compton gamma-ray camera and pan-tilt illuminating device. The robot autonomously steps forward, locates the radiation source, and points it out with the illuminator. [ Paper ] On March 6th, 2025, the Robomechanics Lab at CMU was flooded with 4 feet of black water (i.e. mixed with sewage). We lost most of the robots in the lab, and as a tribute my students put together this “In Memoriam” video. It includes some previously unreleased robots and video clips. [ Carnegie Mellon University Robomechanics Lab ] There haven’t been a lot of successful education robots , but here’s one of them. [ Sphero ] The opening keynote from the 2025 Silicon Valley Humanoids Summit: “Insights Into Disney’s Robotic Character Platform,” by Moritz Baecher, Director, Zurich Lab, Disney Research. [ Humanoids Summit ]

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Video Friday: A Robot Hand With Artificial Muscles and Tendons

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA Enjoy today’s videos! The functional replication and actuation of complex structures inspired by nature is a longstanding goal for humanity. Creating such complex structures combining soft and rigid features and actuating them with artificial muscles would further our understanding of natural kinematic structures. We printed a biomimetic hand in a single print process comprised of a rigid skeleton, soft joint capsules, tendons, and printed touch sensors. [ Paper ] via [ SRL ] Two Boston Dynamics product managers talk about their favorite classic BD robots, and then I talk about mine. And this is Boston Dynamics’ LittleDog, doing legged locomotion research 16 or so years ago in what I’m pretty sure is Katie Byl’s lab at UCSB. [ Boston Dynamics ] This is our latest work on the trajectory planning method for floating-based articulated robots, enabling the global path searching in complex and cluttered environments. [ DRAGON Lab ] Thanks, Moju! OmniPlanner is a unified solution for exploration and inspection path planning (as well as target reach) across aerial, ground, and underwater robots. It has been verified through extensive simulations and a multitude of field tests, including in underground mines, ballast water tanks, forests, university buildings, and submarine bunkers. [ NTNU ] Thanks, Kostas! In the ARISE project, the FZI Research Center for Information Technology and its international partners ETH Zurich, University of Zurich, University of Bern, and University of Basel took a major step toward future lunar missions by testing cooperative autonomous multi-robot teams under outdoor conditions. [ FZI ] Welcome to the future, where there are no other humans. [ Zhejiang Humanoid ] This is our latest work on robotic fish, and is also the first underwater robot of DRAGON Lab. [ DRAGON Lab ] Thanks, Moju! Watch this one simple trick to make humanoid robots cheaper and safer! [ Zhejiang Humanoid ] Gugusse and the Automaton’ is a 1897 French film by Georges Méliès featuring a humanoid robot in nearly as realistic of a way as some of the humanoid promo videos we’ve seen lately. [ Library of Congress ] via [ Gizmodo ] At Agility, we create automated solutions for the hardest work. We’re incredibly proud of how far we’ve come, and can’t wait to show you what’s next. [ Agility ] Kamel Saidi , Robotics Program Manager at the National Institute of Standards and Technology (NIST) , on How Performance Standards can Pave the Way for Humanoid Adoption. [ Humanoids Summit ] Anca Dragan is no stranger to Waymo. She worked with us for six years while also at UC Berkeley and now, Google DeepMind. Her focus on making AI safer helped Waymo as it launched commercially. In this final episode of our season, Anca describes how her work enables AI agents to work fluently with people, based on human goals and values. [ Waymo Podcast ] This UPenn GRASP SFI Seminar is by Junyao Shi, on “Unlocking Generalist Robots with Human Data and Foundation Models.” Building general-purpose robots remains fundamentally constrained by data scarcity and labor-intensive engineering. Unlike vision and language, robotics lacks large, diverse datasets spanning tasks, environments, and embodiments, limiting both scalability and generalization. This talk explores how human data and foundation models trained at scale can help overcome these bottlenecks. [ UPenn ]

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