5 papers
Learning from Demonstration with Failure Awareness for Safe Robot Navigation
Xianghui Wang, Siwei Cheng, Shanze Wang +3
Learning from demonstration is widely used for robot navigation, yet it suffers from a fundamental limitation: demonstrations consist predominantly of successful behaviors and prov…
MA-ROESL: Motion-aware Rapid Reward Optimization for Efficient Robot Skill Learning from Single Videos
Xianghui Wang, Xinming Zhang, Yanjun Chen +2
Vision-language models (VLMs) have demonstrated excellent high-level planning capabilities, enabling locomotion skill learning from video demonstrations without the need for meticu…
Enhancing Deep Reinforcement Learning-based Robot Navigation Generalization through Scenario Augmentation
Shanze Wang, Mingao Tan, Zhibo Yang +4
This work focuses on enhancing the generalization performance of deep reinforcement learning-based robot navigation in unseen environments. We present a novel data augmentation app…
Rethinking Soft Actor-Critic in High-Dimensional Action Spaces: The Cost of Ignoring Distribution Shift
Yanjun Chen, Xinming Zhang, Xianghui Wang +3
Soft Actor-Critic algorithm is widely recognized for its robust performance across a range of deep reinforcement learning tasks, where it leverages the tanh transformation to const…
Achieving Stable High-Speed Locomotion for Humanoid Robots with Deep Reinforcement Learning
Xinming Zhang, Xianghui Wang, Lerong Zhang +3
Humanoid robots offer significant versatility for performing a wide range of tasks, yet their basic ability to walk and run, especially at high velocities, remains a challenge. Thi…