Push-MOG: Efficient Pushing to Consolidate Polygonal Objects for Multi-Object Grasping

Autor:	Aeron, Shrey, LLontop, Edith, Adler, Aviv, Agboh, Wisdom C., Dogar, Mehmet R, Goldberg, Ken
Rok vydání:	2023
Předmět:	Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	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. Comment: 6 pages, 4 figures, CASE 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.14021 Zobrazit plný text záznamu View this record from Arxiv