Multi-object Grasping in the Plane

Wisdom C. Agboh, Jeffrey Ichnowski, Ken Goldberg, Mehmet Remzi Dogar

Abstract: We consider a novel problem where multiple rigid convex polygonal objects rest in randomly placed positions and orientations on a planar surface visible from an overhead camera. The objective is to efficiently grasp and transport all objects into a bin using multi-object push-grasps, where multiple objects are pushed together to facilitate multi-object grasping. We provide necessary conditions for frictionless multi-object push-grasps and apply these to filter inadmissible grasps in a novel multi-object grasp planner. We find that our planner is 19 times faster than a Mujoco simulator baseline. We also propose a picking algorithm that uses both single- and multi-object grasps to pick objects. In physical grasping experiments comparing performance with a single-object picking baseline, we find that the frictionless multi-object grasping system achieves 13.6% higher grasp success and is 59.9% faster, from 212 PPH to 340 PPH. See https://sites.google.com/view/multi-object-grasping for videos and code.