IMR OpenIR
A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots
Li, Yuankai1,2; Ding, Liang3; Zheng, Zhizhong4; Yang, Qizhi2,5; Zhao, Xingang2; Liu, Guangjun6
Corresponding AuthorLi, Yuankai(yuankai.li@uestc.edu.cn) ; Ding, Liang(liangding@hit.edu.cn)
2018-05-01
Source PublicationMECHANICAL SYSTEMS AND SIGNAL PROCESSING
ISSN0888-3270
Volume104Pages:758-775
AbstractFor 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.
KeywordTerrain parameters Real-time estimation Multi-mode recursive Gauss-Newton method adaptive robust extended Kalman filter
Funding OrganizationNatural 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
DOI10.1016/j.ymssp.2017.11.038
Indexed BySCI
Language英语
Funding ProjectNatural 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 Research AreaEngineering
WOS SubjectEngineering, Mechanical
WOS IDWOS:000423652800049
PublisherACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
Citation statistics
Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/127555
Collection中国科学院金属研究所
Corresponding AuthorLi, Yuankai; Ding, Liang
Affiliation1.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
Recommended Citation
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.
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