4 papers
CRL-VLA: Continual Vision-Language-Action Learning
Qixin Zeng, Shuo Zhang, Hongyin Zhang +6
Lifelong learning is critical for embodied agents in open-world environments, where reinforcement learning fine-tuning has emerged as an important paradigm to enable Vision-Languag…
Learning Robotic Policy with Imagined Transition: Mitigating the Trade-off between Robustness and Optimality
Wei Xiao, Shangke Lyu, Zhefei Gong +2
Existing quadrupedal locomotion learning paradigms usually rely on extensive domain randomization to alleviate the sim2real gap and enhance robustness. It trains policies with a wi…
Dynamic Adaptive Legged Locomotion Policy via Decoupling Reaction Force Control and Gait Control
Renjie Wang, Shangke Lyu, Donglin Wang
While Reinforcement Learning (RL) has achieved remarkable progress in legged locomotion control, it often suffers from performance degradation in out-of-distribution (OOD) conditio…
Integrating Trajectory Optimization and Reinforcement Learning for Quadrupedal Jumping with Terrain-Adaptive Landing
Renjie Wang, Shangke Lyu, Xin Lang +2
Jumping constitutes an essential component of quadruped robots' locomotion capabilities, which includes dynamic take-off and adaptive landing. Existing quadrupedal jumping studies…