4 citations · 12 across the 9 of their papers we have counts for
9 papers
Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss
Xinghao Zhu, Yefan Zhou, Yongxiang Fan +3
Robotic grasping for a diverse set of objects is essential in many robot manipulation tasks. One promising approach is to learn deep grasping models from large training datasets of…
6-DoF Contrastive Grasp Proposal Network
Xinghao Zhu, Lingfeng Sun, Yongxiang Fan +1
Proposing grasp poses for novel objects is an essential component for any robot manipulation task. Planning six degrees of freedom (DoF) grasps with a single camera, however, is ch…
Optimization Model for Planning Precision Grasps with Multi-Fingered Hands
Yongxiang Fan, Xinghao Zhu, Masayoshi Tomizuka
Precision grasps with multi-fingered hands are important for precise placement and in-hand manipulation tasks. Searching precision grasps on the object represented by point cloud,…
Efficient Grasp Planning and Execution with Multi-Fingered Hands by Surface Fitting
Yongxiang Fan, Masayoshi Tomizuka
This paper introduces a framework to plan grasps with multi-fingered hands. The framework includes a multi-dimensional iterative surface fitting (MDISF) for grasp planning and a gr…
A Learning Framework for High Precision Industrial Assembly
Yongxiang Fan, Jieliang Luo, Masayoshi Tomizuka
Automatic assembly has broad applications in industries. Traditional assembly tasks utilize predefined trajectories or tuned force control parameters, which make the automatic asse…
A Learning Framework for Robust Bin Picking by Customized Grippers
Yongxiang Fan, Hsien-Chung Lin, Te Tang +1
Customized grippers have specifically designed fingers to increase the contact area with the workpieces and improve the grasp robustness. However, grasp planning for customized gri…
Real-Time Grasp Planning for Multi-Fingered Hands by Finger Splitting
Yongxiang Fan, Te Tang, Hsien-Chung Lin +1
Grasp planning for multi-fingered hands is computationally expensive due to the joint-contact coupling, surface nonlinearities and high dimensionality, thus is generally not afford…
Grasp Planning for Customized Grippers by Iterative Surface Fitting
Yongxiang Fan, Hsien-Chung Lin, Te Tang +1
Customized grippers have broad applications in industrial assembly lines. Compared with general parallel grippers, the customized grippers have specifically designed fingers to inc…
Real-Time Robust Finger Gaits Planning under Object Shape and Dynamics Uncertainties
Yongxiang Fan, Te Tang, Hsien-Chung Lin +2
Dexterous manipulation has broad applications in assembly lines, warehouses and agriculture. To perform large-scale manipulation tasks for various objects, a multi-fingered robotic…