4 papers
Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation
Tyler Han, Bat Nemekhbold, Siyang Shen +6
Current methods in robot learning are fundamentally bottlenecked by one or more of: hand-designed rewards, simulation modeling, or action supervision (e.g. teleoperation) each requ…
Model Predictive Adversarial Imitation Learning for Planning from Observation
Tyler Han, Yanda Bao, Bhaumik Mehta +8
Human demonstration data is often ambiguous and incomplete, motivating imitation learning approaches that also exhibit reliable planning behavior. A common paradigm to perform plan…
Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics
Tyler Han, Preet Shah, Sidharth Rajagopal +9
Reinforcement Learning (RL) has been pivotal in recent robotics milestones and is poised to play a prominent role in the future. However, these advances can rely on proprietary sim…
Uncertainty-aware Accurate Elevation Modeling for Off-road Navigation via Neural Processes
Sanghun Jung, Daehoon Gwak, Byron Boots +1
Terrain elevation modeling for off-road navigation aims to accurately estimate changes in terrain geometry in real-time and quantify the corresponding uncertainties. Having precise…