ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Sustainable and Intelligent Phytoprotection
This article is part of the Research TopicInnovative Techniques for Precision Agriculture and Big DataView all 12 articles
Path Tracking Control Method for Tracked Agricultural Vehicles Based on Slip-Aware Look-Ahead Point Offset
Provisionally accepted
- 1Xihua University, Chengdu, China
- 2Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Hohhot, China
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To improve the path tracking accuracy of tracked agricultural machinery in complex farmland environments, a slip-aware look-ahead point offset path tracking control method is proposed to address the performance degradation of conventional tracking algorithms under track slip conditions. An extended Kalman filter is developed to fuse RTK–IMU pose data with track wheel-speed feedback, enabling online estimation of the slip ratio. A target-point offset compensation mechanism is constructed using the slip-ratio difference as the input, and the offset angle is optimized using an improved particle swarm optimization algorithm to effectively suppress slip-induced errors. To enhance velocity control smoothness, a first-order low-pass filter is applied to the commanded signals. Simulation results show that the proposed method substantially reduces lateral tracking error and maintains smooth trajectories under severe slip conditions. Field experiments further demonstrate that, at speeds of 0.35 m/s and 0.75 m/s, the proposed method notably decreases the maximum lateral deviation by 78.1% and the average deviation by 50.6% compared with the traditional fuzzy pure-pursuit algorithm. At 0.75 m/s, the maximum and average deviations are markedly reduced by 63.1% and 57.6%, respectively. These outcomes verify the accuracy and robustness of the proposed method under complex operating conditions, providing a promising technical solution for path tracking control of tracked agricultural machinery.
Keywords: Extended Kalman filter, Improved particle swarm optimization, Pure pursuit algorithm, Slip compensation, tracked agricultural machinery
Received: 26 Nov 2025; Accepted: 09 Dec 2025.
Copyright: © 2025 Liu, Han, Yin, Junwei, Mu, Tan and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Huanyu Liu
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