8 papers
HiFun: a Hierarchical Framework for Efficient Functional Dexterous Manipulation Learning
Linyi Huang, Guowei Huai, Weibin Liu +5
While multi-fingered dexterous robot hands have the potential to provide human-level dexterity, using them for functional manipulation remains difficult because task success depend…
OmniContact: Chaining Meta-Skills via Contact Flow for Generalizable Humanoid Loco-Manipulation
Runyi Yu, Xiaoyi Lin, Ji Ma +11
Learning long-horizon humanoid loco-manipulation poses a dual challenge: it requires not only the robust execution of meta-skills but also their seamless, closed-loop chaining equi…
Switch: Learning Agile Skills Switching for Humanoid Robots
Yuen-Fui Lau, Qihan Zhao, Yinhuai Wang +4
Recent advancements in whole-body control through deep reinforcement learning have enabled humanoid robots to achieve remarkable progress in real-world chal lenging locomotion skil…
HumanX: Toward Agile and Generalizable Humanoid Interaction Skills from Human Videos
Yinhuai Wang, Qihan Zhao, Yuen Fui Lau +6
Enabling humanoid robots to perform agile and adaptive interactions has long been a core challenge in robotics. Current approaches are bottlenecked by either the scarcity of realis…
Learning Generalizable Hand-Object Tracking from Synthetic Demonstrations
Yinhuai Wang, Runyi Yu, Hok Wai Tsui +9
We present a system for learning generalizable hand-object tracking controllers purely from synthetic data, without requiring any human demonstrations. Our approach makes two key c…
Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop
Tianxing Chen, Kaixuan Wang, Zhaohui Yang +96
Embodied Artificial Intelligence (Embodied AI) is an emerging frontier in robotics, driven by the need for autonomous systems that can perceive, reason, and act in complex physical…
SkillMimic-V2: Learning Robust and Generalizable Interaction Skills from Sparse and Noisy Demonstrations
Runyi Yu, Yinhuai Wang, Qihan Zhao +4
We address a fundamental challenge in Reinforcement Learning from Interaction Demonstration (RLID): demonstration noise and coverage limitations. While existing data collection app…
SkillMimic: Learning Basketball Interaction Skills from Demonstrations
Yinhuai Wang, Qihan Zhao, Runyi Yu +10
Traditional reinforcement learning methods for human-object interaction (HOI) rely on labor-intensive, manually designed skill rewards that do not generalize well across different…