activity
20242026
most citedExploiting Hybrid Policy in Reinforcement Learning for Interpretable Temporal Logic Manipulation

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

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

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…

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.CV2025

Resource-Efficient Affordance Grounding with Complementary Depth and Semantic Prompts

Yizhou Huang, Fan Yang, Guoliang Zhu +6

Affordance refers to the functional properties that an agent perceives and utilizes from its environment, and is key perceptual information required for robots to perform actions.…

cs.CV2025

One-Shot Affordance Grounding of Deformable Objects in Egocentric Organizing Scenes

Wanjun Jia, Fan Yang, Mengfei Duan +6

Deformable object manipulation in robotics presents significant challenges due to uncertainties in component properties, diverse configurations, visual interference, and ambiguous…

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…