7 citations · 15 across the 8 of their papers we have counts for
8 papers
Learning Cross-hand Policies for High-DOF Reaching and Grasping
Qijin She, Shishun Zhang, Yunfan Ye +2
Reaching-and-grasping is a fundamental skill for robotic manipulation, but existing methods usually train models on a specific gripper and cannot be reused on another gripper. In t…
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…
Joint Search of Optimal Topology and Trajectory for Planar Linkages
Zherong Pan, Min Liu, Xifeng Gao +1
We present an algorithm to compute planar linkage topology and geometry, given a user-specified end-effector trajectory. Planar linkage structures convert rotational or prismatic m…
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-…
New Formulation of Mixed-Integer Conic Programming for Globally Optimal Grasp Planning
Min Liu, Zherong Pan, Kai Xu +1
We present a two-level branch-and-bound (BB) algorithm to compute the optimal gripper pose that maximizes a grasp metric in a restricted search space. Our method can take the gripp…
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…
Recurrent 3D Attentional Networks for End-to-End Active Object Recognition
Min Liu, Yifei Shi, Lintao Zheng +3
Active vision is inherently attention-driven: The agent actively selects views to attend in order to fast achieve the vision task while improving its internal representation of the…