2 papers
cs.RO2026
Informationally Decoupled Trajectory Design for Sim-to-Real System Identification
Sangwoo Shin, Ashvin Anilkumar, Ryan Gao +1
Sampling-based system identification estimates physically meaningful parameters by tuning a simulator to reproduce the target system dynamics, providing an interpretable approach t…
cs.RO2026
Reinforcement Learning from Real-Robot Interaction without High-Quality State Estimates
Ryan Gao, Ashvin Anilkumar, Nicholas Corrado +2
A longstanding goal for robot reinforcement learning (RL) is that robots learn from their own physical experience, as humans and animals do. A key obstacle to learning directly fro…