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Robust form-closure grasp planning for 4-pin gripper using learning-based Attractive Region in Environment

文献类型：期刊论文

作者Li, Xiaoqing3; Qian, Yang1; Li, Rui1,2; Niu, Xingyu4; Qiao, Hong1,5
刊名NEUROCOMPUTING
出版日期2020-04-07
卷号384页码:268-281
关键词Attractive Region in Environment (ARIE) Generalized robotic grasping Learning-based grasping 4-pin gripper design
ISSN号0925-2312
DOI10.1016/j.neucom.2019.12.039
通讯作者Qiao, Hong(hong.qiao@ia.ac.cn)
英文摘要In terms of the closure theory, for 3D objects, it usually requires at least 7 grasp points to ensure a form closure grasp, which is too strict for real applications. Instead, using a 4-point planar grasp is much more practical. In this paper, a robust form-closure grasping planning algorithm is proposed for a 4-pin gripper to obtain stable grasp points and improve the generalization to grasp objects that have not been seen before. Besides, a lightweight, 3-DoF (Degree of Freedom) 4-pin gripper based on our algorithm is designed for 3D object grasping. The proposed algorithm consists of two parts. First, based on Attractive Region in Environment (ARIE), the stability of the whole grasping process by obtaining form-closure grasp points is ensured. Second, considering the uncertainty of the environment, a learning grasp quality measurement is proposed to make evaluation of robustness for each group of grasp points. Our simulation and physical experiments are performed to test and verify the effectiveness of the gripper and the proposed algorithm. (C) 2019 Elsevier B.V. All rights reserved.
WOS关键词OBJECTS
资助项目Beijing Natural Science Foundation[L172052] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[61702516] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32050100] ; development of science and technology of Guangdong province special fund project[2016B090910001]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000513853600023
出版者ELSEVIER
资助机构Beijing Natural Science Foundation ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Science ; development of science and technology of Guangdong province special fund project
源URL[http://ir.ia.ac.cn/handle/173211/38457]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
通讯作者Qiao, Hong
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
2.Tech Univ Munich, Munich, Germany
3.Univ Sci & Technol Beijing, Intelligent Robot Ctr, Beijing, Peoples R China
4.Univ Sci & Technol Beijing, Sch Mech Engn, Beijing, Peoples R China
5.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Li, Xiaoqing,Qian, Yang,Li, Rui,et al. Robust form-closure grasp planning for 4-pin gripper using learning-based Attractive Region in Environment[J]. NEUROCOMPUTING,2020,384:268-281.
APA Li, Xiaoqing,Qian, Yang,Li, Rui,Niu, Xingyu,&Qiao, Hong.(2020).Robust form-closure grasp planning for 4-pin gripper using learning-based Attractive Region in Environment.NEUROCOMPUTING,384,268-281.
MLA Li, Xiaoqing,et al."Robust form-closure grasp planning for 4-pin gripper using learning-based Attractive Region in Environment".NEUROCOMPUTING 384(2020):268-281.

入库方式： OAI收割

来源：自动化研究所

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