End-Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor

doi:10.1155/2021/5550850

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	End-Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor
	Luo, Mingrui 3,4; Li, En 4; Guo, Rui 2; Liu, Jiaxin 1; Liang, Zize 4
刊名	JOURNAL OF SENSORS
	2021-04-16
卷号	2021 页码:18
ISSN号	1687-725X
DOI	10.1155/2021/5550850
通讯作者	Li, En(en.li@ia.ac.cn)
英文摘要	Redundant manipulators are suitable for working in narrow and complex environments due to their flexibility. However, a large number of joints and long slender links make it hard to obtain the accurate end-effector pose of the redundant manipulator directly through the encoders. In this paper, a pose estimation method is proposed with the fusion of vision sensors, inertial sensors, and encoders. Firstly, according to the complementary characteristics of each measurement unit in the sensors, the original data is corrected and enhanced. Furthermore, an improved Kalman filter (KF) algorithm is adopted for data fusion by establishing the nonlinear motion prediction of the end-effector and the synchronization update model of the multirate sensors. Finally, the radial basis function (RBF) neural network is used to adaptively adjust the fusion parameters. It is verified in experiments that the proposed method achieves better performances on estimation error and update frequency than the original extended Kalman filter (EKF) and unscented Kalman filter (UKF) algorithm, especially in complex environments.
资助项目	National Key R&D Program of China[2018YFB1307400] ; National Natural Science Foundation of China[61873267]
WOS关键词	DRIVEN PARALLEL ROBOTS ; KINEMATICS ; SYSTEM ; MANIPULATORS ; LOAD
WOS研究方向	Engineering ; Instruments & Instrumentation
语种	英语
出版者	HINDAWI LTD
WOS记录号	WOS:000646709200002
资助机构	National Key R&D Program of China ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/44636]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者	Li, En
作者单位	1.State Grid Liaoning Elect Power Co Ltd, Shenyang, Peoples R China 2.State Grid Shandong Elect Power Co, Jinan, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Luo, Mingrui,Li, En,Guo, Rui,et al. End-Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor[J]. JOURNAL OF SENSORS,2021,2021:18.
APA	Luo, Mingrui,Li, En,Guo, Rui,Liu, Jiaxin,&Liang, Zize.(2021).End-Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor.JOURNAL OF SENSORS,2021,18.
MLA	Luo, Mingrui,et al."End-Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor".JOURNAL OF SENSORS 2021(2021):18.