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Adaptive Path Tracking for Unmanned Ground Vehicle
Zhang MW(张梦巍); Tian FJ(田凤杰); He YQ(何玉庆); Li DC(李德才)
Department机器人学研究室
Conference Name2017 International Conference on Unmanned Systems (IEEE ICUS 2017)
Conference DateOctober 27-29, 2017
Conference PlaceBeijing, China
Source Publication2017 International Conference on Unmanned Systems (IEEE ICUS 2017)
PublisherIEEE
Publication PlaceNew York
2017
Pages139-145
Indexed ByEI ; CPCI(ISTP)
EI Accession number20183205655304
WOS IDWOS:000425254100026
Contribution Rank2
ISBN978-1-5386-3107-2
KeywordUnmanned Ground Vehicle (Ugv) Pure Pursuit Algorithm (Ppa) The Look-ahead Distance Distance Error
Abstract

UGV (Unmanned Ground Vehicle) have many potential applications in a variety of areas. Path tracking is a crucial issue for UGV and one of the most popular methods for path tracking is the PPA (Pure Pursuit Algorithm). Most of researches using the PPA only consider the look-ahead distance as a constant parameter or a function. Whereas in fact, the look-ahead distance is affected by some elements and it would directly influence the effect of path tracking. In this paper, an adaptive path tracking method based on the PPA for UGV is proposed, in which the look-ahead distance is selected in a range of value by comparing distance error between the planned path and the actual path. This proposed method will reduce tracking error in some road condition. The results of experiments show that, compared with the classical PPA, the performance in the effectiveness and accuracy of using the adaptive path tracking method is improved.

Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/21340
Collection机器人学研究室
Corresponding AuthorZhang MW(张梦巍)
Affiliation1.School of mechanical engineering, Shenyang Ligong University, Shenyang, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang MW,Tian FJ,He YQ,et al. Adaptive Path Tracking for Unmanned Ground Vehicle[C]. New York:IEEE,2017:139-145.
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