A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots

doi:10.1016/j.ymssp.2017.11.038

IMR OpenIR

	A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots
	Li, Yuankai 1,2; Ding, Liang 3; Zheng, Zhizhong 4; Yang, Qizhi 2,5; Zhao, Xingang 2; Liu, Guangjun 6
通讯作者	Li, Yuankai(yuankai.li@uestc.edu.cn) ; Ding, Liang(liangding@hit.edu.cn)
	2018-05-01
发表期刊	MECHANICAL SYSTEMS AND SIGNAL PROCESSING
ISSN	0888-3270
卷号	104 页码:758-775
摘要	For motion control of wheeled planetary rovers traversing on deformable terrain, real-time terrain parameter estimation is critical in modeling the wheel-terrain interaction and compensating the effect of wheel slipping. A multi-mode real-time estimation method is proposed in this paper to achieve accurate terrain parameter estimation. The proposed method is composed of an inner layer for real-time filtering and an outer layer for online update. In the inner layer, sinkage exponent and internal frictional angle, which have higher sensitivity than that of the other terrain parameters to wheel-terrain interaction forces, are estimated in real time by using an adaptive robust extended Kalman filter (AREKF), whereas the other parameters are fixed with nominal values. The inner layer result can help synthesize the current wheel-terrain contact forces with adequate precision, but has limited prediction capability for time-variable wheel slipping. To improve estimation accuracy of the result from the inner layer, an otter layer based on recursive Gauss-Newton (RGN) algorithm is introduced to refine the result of real-time filtering according to the innovation contained in the history data. With the two-layer structure, the proposed method can work in three fundamental estimation modes: EKF, REKF and RGN, making the method applicable for flat, rough and non-Uniform terrains. Simulations have demonstrated the effectiveness of the proposed method under three terrain types, showing the advantages of introducing the two-layer structure. (C) 2017 Elsevier Ltd. All rights reserved.
关键词	Terrain parameters Real-time estimation Multi-mode recursive Gauss-Newton method adaptive robust extended Kalman filter
资助者	Natural Sciences and Engineering Research Council (NSERC) ; Canada Research Chair (CRC) ; China State Key Laboratory of Robotics ; SRF ; SEM ; China Fundamental Research Funds for the Central Universities
DOI	10.1016/j.ymssp.2017.11.038
收录类别	SCI
语种	英语
资助项目	Natural Sciences and Engineering Research Council (NSERC) ; Canada Research Chair (CRC) ; China State Key Laboratory of Robotics[2013-O08] ; SRF ; SEM ; China Fundamental Research Funds for the Central Universities[ZYGX-2014-J098]
WOS研究方向	Engineering
WOS类目	Engineering, Mechanical
WOS记录号	WOS:000423652800049
出版者	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
引用统计	被引频次：23[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/127555
专题	中国科学院金属研究所
通讯作者	Li, Yuankai; Ding, Liang
作者单位	1.Univ Elect Sci & Technol China, Sch Aeronaut & Astronaut, Chengdu, Sichuan, Peoples R China 2.Chinese Acad Sci, Shenyang Inst Automat, Shenyang, Liaoning, Peoples R China 3.Harbin Inst Technol, State Key Lab Robot & Syst, Harbin, Heilongjiang, Peoples R China 4.Natl Engn & Technol Res Ctr Digital Switching Sys, Zhengzhou, Henan, Peoples R China 5.Jiangsu Univ, Sch Mech Engn, Zhenjiang, Peoples R China 6.Ryerson Univ, Dept Aerosp Engn, Toronto, ON, Canada
推荐引用方式 GB/T 7714	Li, Yuankai,Ding, Liang,Zheng, Zhizhong,et al. A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING,2018,104:758-775.
APA	Li, Yuankai,Ding, Liang,Zheng, Zhizhong,Yang, Qizhi,Zhao, Xingang,&Liu, Guangjun.(2018).A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots.MECHANICAL SYSTEMS AND SIGNAL PROCESSING,104,758-775.
MLA	Li, Yuankai,et al."A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots".MECHANICAL SYSTEMS AND SIGNAL PROCESSING 104(2018):758-775.