10 papers
GCNGrasp-VP: Affordance-Guided View Planning for Efficient Task-Oriented Grasping
Zanjia Tong, Wenlong Dong, Chengjie Zhang +1
Task-oriented grasping performance degrades significantly when object views suffer from occlusions. Existing task-oriented grasping methods typically assume task-relevant regions a…
VLAConf: Calibrated Task-Success Confidence for Vision-Language-Action Models
Dehao Huang, Aoxiang Gu, Chengjie Zhang +5
Task-success confidence estimation for Vision-Language-Action (VLA) models provides a crucial task-level signal for monitoring manipulation in open-world environments and supportin…
Grasp as You Dream: Imitating Functional Grasping from Generated Human Demonstrations
Chao Tang, Jiacheng Xu, Haofei Lu +4
Building generalist robots capable of performing functional grasping in everyday, open-world environments remains a significant challenge due to the vast diversity of objects and t…
Easy-IIL: Reducing Human Operational Burden in Interactive Imitation Learning via Assistant Experts
Chengjie Zhang, Chao Tang, Wenlong Dong +3
Interactive Imitation Learning (IIL) typically relies on extensive human involvement for both offline demonstration and online interaction. Prior work primarily focuses on reducing…
MimicFunc: Imitating Tool Manipulation from a Single Human Video via Functional Correspondence
Chao Tang, Anxing Xiao, Yuhong Deng +5
Imitating tool manipulation from human videos offers an intuitive approach to teaching robots, while also providing a promising and scalable alternative to labor-intensive teleoper…
HGDiffuser: Efficient Task-Oriented Grasp Generation via Human-Guided Grasp Diffusion Models
Dehao Huang, Wenlong Dong, Chao Tang +1
Task-oriented grasping (TOG) is essential for robots to perform manipulation tasks, requiring grasps that are both stable and compliant with task-specific constraints. Humans natur…