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

doi:10.1016/j.neucom.2019.12.039

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Robust form-closure grasp planning for 4-pin gripper using learning-based Attractive Region in Environment
	Li, Xiaoqing1 ; Qian, Yang3 ; Li, Rui3,5 ; Niu, Xingyu2 ; Qiao, Hong3,4
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
	2020-04-07
卷号	384 页码:268-281
通讯作者	Qiao, Hong(hong.qiao@ia.ac.cn)
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.
关键词	Attractive Region in Environment (ARIE) Generalized robotic grasping Learning-based grasping 4-pin gripper design
DOI	10.1016/j.neucom.2019.12.039
关键词[WOS]	OBJECTS
收录类别	SCI
语种	英语
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] ; 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]
项目资助者	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
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000513853600023
出版者	ELSEVIER
七大方向——子方向分类	智能机器人
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/38458
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Qiao, Hong
作者单位	1.Univ Sci & Technol Beijing, Intelligent Robot Ctr, Beijing, Peoples R China 2.Univ Sci & Technol Beijing, Sch Mech Engn, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Tech Univ Munich, Munich, Germany
通讯作者单位	中国科学院自动化研究所
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.