Abstract
This talk explores how to push the boundaries of robotic autonomy and mobility. We review the current state of adaptive legged locomotion and navigation policies, and discuss pathways toward policies that generalize beyond their developers’ original intentions. We examine how such policies can be trained across diverse modalities and data sources, spanning simulation and the real world. In addition, we explore the role of reasoning in handling out-of-distribution scenarios, motivating the development of new scene representations for mobile robots. Finally, we argue that grounding autonomy in first principles can enable more robust and general robotic systems, improving safety while accelerating their deployment in real-world environments.
Bio
Dr. Jonas Frey is a Postdoctoral Researcher at Stanford’s Autonomous Systems Lab and UC Berkeley’s BAIR, working with Prof. Marco Pavone and Prof. Jitendra Malik. His research focuses on RL-based perception and navigation for legged robots, specifically on combining embodied policies with foundation models. Dr. Frey earned his Ph.D. from ETH Zurich and the Max Planck Institute. His extensive collaborative background includes stints at NASA JPL, the University of Oxford, and NAIST (Japan), as well as industrial experience as a robotics engineer at SEW-EURODRIVE.
