8 papers
HUGS: Guiding Unified Dexterous Grasp Synthesis Across Modes and Scales via Learned Human Priors
Mingrui Yu, Yongpeng Jiang, Yongyi Jia +4
Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synthesis methods reduce the hig…
CoorGrasp: Coordinated Contact Control for Adaptive Dexterous Grasping Under Uncertainty
Mingrui Yu, Yongpeng Jiang, Yongyi Jia +3
While recent research has focused heavily on dexterous grasp pose generation, less attention has been devoted to the execution of planned grasps. Under shape and position uncertain…
EmbodiSteer: Steering Embodiment-Agnostic Visuomotor Policies with Joint-Space Guidance for Zero-Shot Cross-Embodiment Deployment
Shihefeng Wang, Kangchen Lv, Mingrui Yu +1
Scalable robot imitation learning relies on large-scale heterogeneous data from diverse robots or body-free data, making Cartesian end-effector actions a key interface for embodime…
Analyzing Key Objectives in Human-to-Robot Retargeting for Dexterous Manipulation
Chendong Xin, Mingrui Yu, Yongpeng Jiang +2
Kinematic retargeting from human hands to robot hands is essential for transferring dexterity from humans to robots in manipulation teleoperation and imitation learning. However, d…
UniStateDLO: Unified Generative State Estimation and Tracking of Deformable Linear Objects Under Occlusion for Constrained Manipulation
Kangchen Lv, Mingrui Yu, Shihefeng Wang +2
Perception of deformable linear objects (DLOs), such as cables, ropes, and wires, is the cornerstone for successful downstream manipulation. Although vision-based methods have been…
Kinematics-Aware Diffusion Policy with Consistent 3D Observation and Action Space for Whole-Arm Robotic Manipulation
Kangchen Lv, Mingrui Yu, Yongyi Jia +2
Whole-body control of robotic manipulators with awareness of full-arm kinematics is crucial for many manipulation scenarios involving body collision avoidance or body-object intera…