ShakingBot: Dynamic Manipulation for Bagging

Fuente: arXiv
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Autori principali: Gu, Ningquan, Zhang, Zhizhong, He, Ruhan, Yu, Lianqing
Natura: Preprint
Pubblicazione: 2023
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author Gu, Ningquan
Zhang, Zhizhong
He, Ruhan
Yu, Lianqing
author_facet Gu, Ningquan
Zhang, Zhizhong
He, Ruhan
Yu, Lianqing
contents Bag manipulation through robots is complex and challenging due to the deformability of the bag. Based on dynamic manipulation strategy, we propose a new framework, ShakingBot, for the bagging tasks. ShakingBot utilizes a perception module to identify the key region of the plastic bag from arbitrary initial configurations. According to the segmentation, ShakingBot iteratively executes a novel set of actions, including Bag Adjustment, Dual-arm Shaking, and One-arm Holding, to open the bag. The dynamic action, Dual-arm Shaking, can effectively open the bag without the need to account for the crumpled configuration.Then, we insert the items and lift the bag for transport. We perform our method on a dual-arm robot and achieve a success rate of 21/33 for inserting at least one item across various initial bag configurations. In this work, we demonstrate the performance of dynamic shaking actions compared to the quasi-static manipulation in the bagging task. We also show that our method generalizes to variations despite the bag's size, pattern, and color.
format Preprint
id arxiv_https___arxiv_org_abs_2304_04558
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle ShakingBot: Dynamic Manipulation for Bagging
Gu, Ningquan
Zhang, Zhizhong
He, Ruhan
Yu, Lianqing
Robotics
Bag manipulation through robots is complex and challenging due to the deformability of the bag. Based on dynamic manipulation strategy, we propose a new framework, ShakingBot, for the bagging tasks. ShakingBot utilizes a perception module to identify the key region of the plastic bag from arbitrary initial configurations. According to the segmentation, ShakingBot iteratively executes a novel set of actions, including Bag Adjustment, Dual-arm Shaking, and One-arm Holding, to open the bag. The dynamic action, Dual-arm Shaking, can effectively open the bag without the need to account for the crumpled configuration.Then, we insert the items and lift the bag for transport. We perform our method on a dual-arm robot and achieve a success rate of 21/33 for inserting at least one item across various initial bag configurations. In this work, we demonstrate the performance of dynamic shaking actions compared to the quasi-static manipulation in the bagging task. We also show that our method generalizes to variations despite the bag's size, pattern, and color.
title ShakingBot: Dynamic Manipulation for Bagging
topic Robotics
url https://arxiv.org/abs/2304.04558