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cs.RO2026

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…

cs.RO2026

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…

cs.RO2025

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…

cs.RO2025

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…

cs.RO2025

Learning Granularity-Aware Affordances from Human-Object Interaction for Tool-Based Functional Dexterous Grasping

Fan Yang, Wenrui Chen, Kailun Yang +5

To enable robots to use tools, the initial step is teaching robots to employ dexterous gestures for touching specific areas precisely where tasks are performed. Affordance features…