Nearly a year ago I started my role at BYU as Assistant Professor in Mechanical Engineering. Together with Josh Mangelson, we lead the FROST Lab (frostlab.byu.edu), developing robotic systems for robust operation in complex real-world environments, including planning, perception, SLAM, and more.

Excited to share that IA-TIGRIS, a major part of my PhD work, has been published in IEEE Transactions on Robotics! Hundreds of flights and extensive validation toward practical online informative path planning for real robots. ia-tigris.github.io

IA-TIGRIS: An Incremental and Adaptive Sampling-based Planner for Online Informative Path Planning

We present IA-TIGRIS, an incremental and adaptive sampling-based informative path planner that can be run efficiently with onboard computation.

ia-tigris.github.io

I’m excited to share that I have officially defended my PhD thesis. This journey was built on a lot of hard work, great mentorship, and the support of a community I'm deeply thankful for. You can watch the defense here: youtu.be/mWyqYeOTZIs

Brady Moon PhD Thesis Defense | Carnegie Mellon University | Robotics Institute

YouTube video by Brady Moon

youtu.be

🛻🌳 Autonomous Off-Road Driving – No Labels, No Prior Map, & No GPS! Our self-supervised stack enables an ATV to navigate forests, snow, & nighttime. (1/5) More details: theairlab.org/offroad/ Full video: youtu.be/7t4EQj8BIdY #cmurobotics #robotics #autonomy @cmurobotics.bsky.social

Autonomous Offroad Driving: A Full Run of Self-supervised, Multi-modal, Uncertainty-aware Autonomy

YouTube video by AirLab

youtu.be

Excited to share our work MapEx at #ICRA2025! We tackle the challenge of efficient exploration by leveraging a global map predictor. This is also my first post here—I’m Brady, and I research autonomous systems and informative path planning. Looking forward to connecting! mapex-explorer.github.io

Seungchan Kim@seungchankim.bsky.social · last yr.

Excited to announce MapEx is accepted to ICRA 2025! 🚀 🤖🕵️‍♀️How can a robot explore to build accurate maps without seeing everything? mapex-explorer.github.io We explore by jointly reasoning on prediction uncertainty and potential sensor coverage using multiple map predictions of unseen areas. 1/n