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TONAV: Task-Oriented Navigation and Action-Velocity Chunk Learning for Articulated Object Quadrupedal Mobile Manipulation
Haoran Lin, Mingyu Yang, Pengfei Qi +6
Quadruped mobile manipulation requires two tightly coupled capabilities: reaching manipulation-ready configurations and maintaining stable contact throughout articulated-object int…
DexPIE: Stable Dexterous Policy Improvement from Real-World Experience
Ruizhe Liao, Wenrui Chen, Liangji Zeng +4
Dexterous manipulation presents substantial challenges for imitation learning due to its high-dimensional action space and complex contact-rich dynamics. Policies trained purely fr…
TRACER: Texture-Robust Affordance Chain-of-Thought for Deformable-Object Refinement
Wanjun Jia, Kang Li, Fan Yang +7
The central challenge in robotic manipulation of deformable objects lies in aligning high-level semantic instructions with physical interaction points under complex appearance and…
Design of an Adaptive Modular Anthropomorphic Dexterous Hand for Human-like Manipulation
Zelong Zhou, Wenrui Chen, Zeyun Hu +3
Biological synergies have emerged as a widely adopted paradigm for dexterous hand design, enabling human-like manipulation with a small number of actuators. Nonetheless, excessive…
UniFucGrasp: Human-Hand-Inspired Unified Functional Grasp Annotation Strategy and Dataset for Diverse Dexterous Hands
Haoran Lin, Wenrui Chen, Xianchi Chen +7
Dexterous grasp datasets are vital for embodied intelligence, but mostly emphasize grasp stability, ignoring functional grasps needed for tasks like opening bottle caps or holding…
Multi-Keypoint Affordance Representation for Functional Dexterous Grasping
Fan Yang, Dongsheng Luo, Wenrui Chen +5
Functional dexterous grasping requires precise hand-object interaction, going beyond simple gripping. Existing affordance-based methods primarily predict coarse interaction regions…