Bimanual Shelf Picking Planner Based on Collapse Prediction

Abstract

In logistics warehouse, since many objects are randomly stacked on shelves, it becomes difficult for a robot to safely extract one of the objects without other objects falling from the shelf. In previous works, a robot needed to extract the target object after rearranging the neighboring objects. In contrast, humans extract an object from a shelf while supporting other neighboring objects. In this paper, we propose a bimanual manipulation planner based on collapse prediction trained with data generated from a physics simulator, which can safely extract a single object while supporting the other objects. We confirmed that the proposed method achieves more than 80% success rate for safe extraction by real-world experiments using a dual-arm manipulator.

Keyword

Manipulation, Grasping with learning-based method, Motion planning.

Bibtex:
@INPROCEEDINGS{9551507, author={Motoda, Tomohiro and Petit, Damien and Wan, Weiwei and Harada, Kensuke}, booktitle={2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)}, title={Bimanual Shelf Picking Planner Based on Collapse Prediction}, year={2021}, volume={}, number={}, pages={510-515}, doi={10.1109/CASE49439.2021.9551507}}

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