Multi-Object Grasping in the Plane
Agboh, Wisdom C., Ichnowski, Jeffrey, Goldberg, Ken, Dogar, Mehmet R.
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Sep-21-2022
- Country:
- Europe > United Kingdom
- England > West Yorkshire > Leeds (0.04)
- North America > United States (0.04)
- Europe > United Kingdom
- Genre:
- Research Report (0.64)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning (0.95)
- Representation & Reasoning (0.93)
- Robots > Manipulation (0.68)
- Information Technology > Artificial Intelligence