Wisdom C. Agboh Jeffrey Ichnowski Ken Goldberg Mehmet Dogar
We consider the 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. Specifically, we explore multi-object push-grasps where multiple objects are pushed together before the grasp can occur. We provide necessary conditions for multi-object push-grasps and apply these to filter inadmissible grasps in a novel multi-object grasp planner. We also propose a picking algorithm that uses both single- and multi-object grasps to pick objects.
Multi-object grasping (8x)
Single object grasping (8x)
Grasp failures due to the multi-object diameter condition
Grasp failures due to the intersection area condition
Main experimental results
Our multi-object grasp planner is 19 times faster than a Mujoco physics simulator baseline.
Our multi-object grasping system achieves 13.6% higher grasp success and is 59.9% faster than a single object picking baseline.