Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds [article]

Lirui Wang, Yu Xiang, Wei Yang, Arsalan Mousavian, Dieter Fox
2021 arXiv   pre-print
6D robotic grasping beyond top-down bin-picking scenarios is a challenging task. Previous solutions based on 6D grasp synthesis with robot motion planning usually operate in an open-loop setting, which are sensitive to grasp synthesis errors. In this work, we propose a new method for learning closed-loop control policies for 6D grasping. Our policy takes a segmented point cloud of an object from an egocentric camera as input, and outputs continuous 6D control actions of the robot gripper for
more » ... sping the object. We combine imitation learning and reinforcement learning and introduce a goal-auxiliary actor-critic algorithm for policy learning. We demonstrate that our learned policy can be integrated into a tabletop 6D grasping system and a human-robot handover system to improve the grasping performance of unseen objects. Our videos and code can be found at https://sites.google.com/view/gaddpg .
arXiv:2010.00824v4 fatcat:w3ut3hdv4jdnfndeaynba2t424