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cs.RO2026
Task-Specified Compliance Bounds for Humanoids via Lipschitz-Constrained Policies
Zewen He, Yoshihiko Nakamura
Reinforcement learning (RL) has demonstrated substantial potential for humanoid bipedal locomotion and the control of complex motions. To cope with oscillations and impacts induced…
cs.RO2025
CoTaP: Compliant Task Pipeline and Reinforcement Learning of Its Controller with Compliance Modulation
Zewen He, Chenyuan Chen, Dilshod Azizov +1
Humanoid whole-body locomotion control is a critical approach for humanoid robots to leverage their inherent advantages. Learning-based control methods derived from retargeted huma…
cs.RO2025
3D-CovDiffusion: 3D-Aware Diffusion Policy for Coverage Path Planning
Chenyuan Chen, Haoran Ding, Ran Ding +6
Diffusion models have shown strong potential for robot skill learning, yet their role in coverage path planning remains underexplored. In industrial surface processing (painting, p…