4 papers
Direction Matters: Learning Force Direction Enables Sim-to-Real Contact-Rich Manipulation
Yifei Yang, Anzhe Chen, Zhenjie Zhu +6
Sim-to-real transfer for contact-rich manipulation remains challenging due to the inherent discrepancy in contact dynamics. While existing methods often rely on costly real-world d…
Disambiguate Gripper State in Grasp-Based Tasks: Pseudo-Tactile as Feedback Enables Pure Simulation Learning
Yifei Yang, Lu Chen, Zherui Song +5
Grasp-based manipulation tasks are fundamental to robots interacting with their environments, yet gripper state ambiguity significantly reduces the robustness of imitation learning…
Natural Humanoid Robot Locomotion with Generative Motion Prior
Haodong Zhang, Liang Zhang, Zhenghan Chen +3
Natural and lifelike locomotion remains a fundamental challenge for humanoid robots to interact with human society. However, previous methods either neglect motion naturalness or r…
Compliance while resisting: a shear-thickening fluid controller for physical human-robot interaction
Lu Chen, Lipeng Chen, Xiangchi Chen +6
Physical human-robot interaction (pHRI) is widely needed in many fields, such as industrial manipulation, home services, and medical rehabilitation, and puts higher demands on the…