10 papers
KPGrasp: Scalable Keypoint Flow Matching for Dexterous Grasp Generation
Yuansen Huang, Jiayi Chen, Haoran Liu +6
Generating high-quality dexterous grasps remains challenging for learning-based methods, which often depend on carefully tuned contact losses or costly contact-based test-time refi…
BiDexGrasp: Coordinated Bimanual Dexterous Grasps across Object Geometries and Sizes
Mu Lin, Yi-Lin Wei, Jiaxuan Chen +7
Bimanual dexterous grasping is a fundamental and promising area in robotics, yet its progress is constrained by the lack of comprehensive datasets and powerful generation models. I…
FoldNet: Learning Generalizable Closed-Loop Policy for Garment Folding via Keypoint-Driven Asset and Demonstration Synthesis
Yuxing Chen, Bowen Xiao, He Wang
Due to the deformability of garments, generating a large amount of high-quality data for robotic garment manipulation tasks is highly challenging. In this paper, we present a synth…
GraspADMM: Improving Dexterous Grasp Synthesis via ADMM Optimization
Liangwang Ruan, Jiayi Chen, He Wang +1
Synthesizing high-quality dexterous grasps is a fundamental challenge in robot manipulation, requiring adherence to diversity, kinematic feasibility (valid hand-object contact with…
Learning Athletic Humanoid Tennis Skills from Imperfect Human Motion Data
Zhikai Zhang, Haofei Lu, Yunrui Lian +12
Human athletes demonstrate versatile and highly-dynamic tennis skills to successfully conduct competitive rallies with a high-speed tennis ball. However, reproducing such behaviors…
TacDexGrasp: Compliant and Robust Dexterous Grasping with Tactile Feedback
Yubin Ke, Jiayi Chen, Hang Lv +2
Multi-fingered hands offer great potential for compliant and robust grasping of unknown objects, yet their high-dimensional force control presents a significant challenge. This wor…