5 papers
ProxiDex: Learning Dynamics-Guided Proximity Policy for Dexterous Manipulation
Yushan Bai, Boyu Zheng, Zhiyang Mao +4
Multi-finger dexterous manipulation relies on stable hand-object interactions, yet these interactions are partially observable in practice. Visual observations are often occluded b…
Causal Reward World Models: Zero-shot Reward Design for Automated Skill Generation
Yang Yang, Yuchuang Tong, Zhengtao Zhang +6
Automated Reward Design (ARD) aims to replace manual reward engineering in reinforcement learning with language-driven reward function synthesis. However, existing approaches based…
FAR-Dex: Few-shot Data Augmentation and Adaptive Residual Policy Refinement for Dexterous Manipulation
Yushan Bai, Fulin Chen, Hongzheng Sun +3
Achieving human-like dexterous manipulation through the collaboration of multi-fingered hands with robotic arms remains a longstanding challenge in robotics, primarily due to the s…
IDAGC: Adaptive Generalized Human-Robot Collaboration via Human Intent Estimation and Multimodal Policy Learning
Haotian Liu, Yuchuang Tong, Guanchen Liu +2
In Human-Robot Collaboration (HRC), which encompasses physical interaction and remote cooperation, accurate estimation of human intentions and seamless switching of collaboration m…
DTRT: Enhancing Human Intent Estimation and Role Allocation for Physical Human-Robot Collaboration
Haotian Liu, Yuchuang Tong, Zhengtao Zhang
In physical Human-Robot Collaboration (pHRC), accurate human intent estimation and rational human-robot role allocation are crucial for safe and efficient assistance. Existing meth…