3 accepted papers
Visuomotor policies learned through imitation learning methods often struggle to generalize to new visual domains due to the limited diversity of expert demonstrations, and collecting extensive real-world data is exhaustive. To address this challenge, we propose a novel demonstration generation app…
Self-improvement requires robotic systems to initially learn from human-provided data and then gradually enhance their capabilities through interaction with the environment. This is similar to how humans improve their skills through continuous practice. However, achieving effective self-improvement
Stable locomotion in precipitous environments is an essential task for quadruped robots, requiring the ability to resist various external disturbances. Recent neural policies enhance robustness against disturbances by learning to resist external forces sampled from a fixed distribution in the simula…