English

Multi-Object Grasping in the Plane

Robotics 2022-09-22 v2 Artificial Intelligence

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 \url{https://sites.google.com/view/multi-object-grasping} for videos and code.

Keywords

Cite

@article{arxiv.2206.00229,
  title  = {Multi-Object Grasping in the Plane},
  author = {Wisdom C. Agboh and Jeffrey Ichnowski and Ken Goldberg and Mehmet R. Dogar},
  journal= {arXiv preprint arXiv:2206.00229},
  year   = {2022}
}

Comments

Accepted to the International Symposium on Robotics Research (ISRR), 2022

R2 v1 2026-06-24T11:35:28.393Z