Multi-Object Grasping in the Plane
This addresses the challenge of multi-object manipulation in robotics, offering incremental improvements in speed and success rates for specific grasping tasks.
The paper tackles the problem of efficiently grasping and transporting multiple rigid convex polygonal objects on a planar surface using multi-object push-grasps, resulting in a planner that is 19 times faster than a baseline and a system that achieves 13.6% higher grasp success and 59.9% faster picking speed (from 212 to 340 PPH).
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 \url{https://sites.google.com/view/multi-object-grasping} for videos and code.