Push-MOG: Efficient Pushing to Consolidate Polygonal Objects for Multi-Object Grasping
June 24, 2023 Β· Declared Dead Β· π 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)
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Authors
Shrey Aeron, Edith LLontop, Aviv Adler, Wisdom C. Agboh, Mehmet R Dogar, Ken Goldberg
arXiv ID
2306.14021
Category
cs.RO: Robotics
Citations
7
Venue
2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)
Last Checked
4 months ago
Abstract
Recently, robots have seen rapidly increasing use in homes and warehouses to declutter by collecting objects from a planar surface and placing them into a container. While current techniques grasp objects individually, Multi-Object Grasping (MOG) can improve efficiency by increasing the average number of objects grasped per trip (OpT). However, grasping multiple objects requires the objects to be aligned and in close proximity. In this work, we propose Push-MOG, an algorithm that computes "fork pushing" actions using a parallel-jaw gripper to create graspable object clusters. In physical decluttering experiments, we find that Push-MOG enables multi-object grasps, increasing the average OpT by 34%. Code and videos will be available at https://sites.google.com/berkeley.edu/push-mog.
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