Vision-Based Imitation Learning of Needle Reaching Skill for Robotic Precision Manipulation

doi:10.1007/s10846-020-01290-1

CORC > 自动化研究所 > 中国科学院自动化研究所 > 精密感知与控制研究中心 > 精密感知与控制

	Vision-Based Imitation Learning of Needle Reaching Skill for Robotic Precision Manipulation
	Li, Ying 2,3; Qin, Fangbo 2,3; Du, Shaofeng 1; Xu, De 2,3; Zhang, Jianqiang 1
刊名	JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
	2021
卷号	101 期号:1 页码:13
关键词	Imitation learning Skill learning Visual control Robotic precision manipulation Neural networks
ISSN号	0921-0296
DOI	10.1007/s10846-020-01290-1
通讯作者	Li, Ying(liying2016@ia.ac.cn)
英文摘要	In this paper, an imitation learning approach of vision guided reaching skill is proposed for robotic precision manipulation, which enables the robot to adapt its end-effector's nonlinear motion with the awareness of collision-avoidance. The reaching skill model firstly uses the raw images of objects as inputs, and generates the incremental motion command to guide the lower-level vision-based controller. The needle's tip is detected in image space and the obstacle region is extracted by image segmentation. A neighborhood-sampling method is designed for needle component collision perception, which includes a neural networks based attention module. The neural network based policy module infers the desired motion in the image space according to the neighborhood-sampling result, goal and current positions of the needle's tip. A refinement module is developed to further improve the performance of the policy module. In three dimensional (3D) manipulation tasks, typically two cameras are used for image-based vision control. Therefore, considering the epipolar constraint, the relative movements in two cameras' views are refined by optimization. Experimental are conducted to validate the effectiveness of the proposed methods.
资助项目	National Key Research and Development Program of China[2018AAA0103005] ; National Natural Science Foundation of China[61873266] ; State Key Laboratory of Smart Manufacturing for Special Vehicles and Transmission System[GZ2019KF008]
WOS关键词	MICROSCOPIC VISION
WOS研究方向	Computer Science ; Robotics
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000600232300001
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; State Key Laboratory of Smart Manufacturing for Special Vehicles and Transmission System
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42786]
专题	精密感知与控制研究中心_精密感知与控制
通讯作者	Li, Ying
作者单位	1.State Key Lab Smart Mfg Special Vehicles & Transm, Baotou City 014000, Inner Mongolia, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Li, Ying,Qin, Fangbo,Du, Shaofeng,et al. Vision-Based Imitation Learning of Needle Reaching Skill for Robotic Precision Manipulation[J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS,2021,101(1):13.
APA	Li, Ying,Qin, Fangbo,Du, Shaofeng,Xu, De,&Zhang, Jianqiang.(2021).Vision-Based Imitation Learning of Needle Reaching Skill for Robotic Precision Manipulation.JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS,101(1),13.
MLA	Li, Ying,et al."Vision-Based Imitation Learning of Needle Reaching Skill for Robotic Precision Manipulation".JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 101.1(2021):13.