1 citations · 1 across the 2 of their papers we have counts for
4 papers
Learning High-DOF Reaching-and-Grasping via Dynamic Representation of Gripper-Object Interaction
Qijin She, Ruizhen Hu, Juzhan Xu +3
We approach the problem of high-DOF reaching-and-grasping via learning joint planning of grasp and motion with deep reinforcement learning. To resolve the sample efficiency issue i…
Deep Differentiable Grasp Planner for High-DOF Grippers
Min Liu, Zherong Pan, Kai Xu +2
We present an end-to-end algorithm for training deep neural networks to grasp novel objects. Our algorithm builds all the essential components of a grasping system using a forward-…
Globally Optimal Joint Search of Topology and Trajectory for Planar Linkages
Zherong Pan, Min Liu, Xifeng Gao +2
We present a method to find globally optimal topology and trajectory jointly for planar linkages. Planar linkage structures can generate complex end-effector trajectories using onl…
Generating Grasp Poses for a High-DOF Gripper Using Neural Networks
Min Liu, Zherong Pan, Kai Xu +2
We present a learning-based method for representing grasp poses of a high-DOF hand using neural networks. Due to redundancy in such high-DOF grippers, there exists a large number o…