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An optimal goal point determination algorithm for automatic navigation of agricultural machinery: Improving the tracking accuracy of the Pure Pursuit algorithm.

Authors :
Yang, Yang
Li, Yankai
Wen, Xing
Zhang, Gang
Ma, Qianglong
Cheng, Shangkun
Qi, Jian
Xu, Liangyuan
Chen, Liqing
Source :
Computers & Electronics in Agriculture. Mar2022, Vol. 194, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• A goal point determination method is proposed for the problem of selecting the optimal path point by Pure Pursuit. • An evaluation function is established to select the optimal goal point based on tractor position prediction model. • The performance of the proposed path tracking algorithm is studied by field test. The development of precision agriculture requires the implementation of automatic navigation technology for agricultural machinery. Path tracking control as one of the key steps in automatic navigation technology has great research value. Pure Pursuit algorithm as a popular control algorithm for automatic navigation technology for agricultural machinery, the look-ahead distance is the key to the tracking effect, while the calculation of look-ahead distance has the problem that many influencing factors are difficult to be accurately described by mathematical expressions, which leads to the difficulty to select a suitable goal point tracking path. In order to solve the above problems, this paper proposes a path tracking algorithm for agricultural machinery based on the optimal goal point. The algorithm simulates the look-ahead behavior of the driver and searches for optimal goal point in the look-ahead area according to the evaluation function. The objective of the study is to minimize the lateral error and heading error to achieve the adaptive optimization of the goal point. Finally, the feasibility of the algorithm proposed in this paper was verified in simulations and bumpy field tests under various different conditions, with tracking errors reduced by more than 20% compared to the pure pursuit algorithm. The tracking accuracy is significantly improved. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01681699
Volume :
194
Database :
Academic Search Index
Journal :
Computers & Electronics in Agriculture
Publication Type :
Academic Journal
Accession number :
155560035
Full Text :
https://doi.org/10.1016/j.compag.2022.106760