Path tracking control method for tracked agricultural vehicles based on slip-aware look-ahead point offset

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Authors: Huanyu Liu, Zhihang Han, Jiaqin Yin, Junwei Lucas Bao, Jian Mu, Hewen Tan, Xiangnan Liu
Cited by: 7
References: 13

Abstract

Introduction: Tracked agricultural vehicles operating in complex farmland environments are prone to track slip, which degrades path-tracking accuracy and may lead to unstable motion. To address the limitations of conventional geometric tracking algorithms under slip conditions, this study proposes a slip-aware look-ahead point offset path-tracking control method for tracked agricultural machinery. Methods: An extended Kalman filter (EKF) is developed to fuse RTK-IMU pose measurements with track wheel-speed feedback, enabling real-time estimation of left and right track slip ratios. Based on the estimated slip difference, a target-point offset compensation mechanism is constructed, and the offset angle is optimized online using an improved particle swarm optimization (PSO) algorithm with a Chebyshev-window-based inertia weight strategy. In addition, a fuzzy controller is employed to adaptively adjust the look-ahead distance according to vehicle speed and path curvature, while a first-order low-pass filter is applied to smooth the commanded velocities. Results: Simulation results demonstrate that the proposed method significantly reduces lateral tracking errors and maintains smooth trajectories under severe slip conditions. Field experiments conducted at speeds of 0.35 m/s and 0.75 m/s show that the proposed method reduces 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 further reduced by 63.1% and 57.6%, respectively. Discussion: The results confirm that incorporating slip estimation and slip-aware target-point offset compensation effectively enhances path-tracking accuracy and robustness for tracked agricultural vehicles operating on soft and high-slip terrain. The proposed lightweight control framework provides a practical and reliable solution for autonomous navigation and plant-protection operations in complex farmland environments.

Fields of Study & Subjects

Control and Dynamics of Mobile Robots Soil Mechanics and Vehicle Dynamics Vehicle Dynamics and Control Systems

Publication details

Journal / source
Frontiers in Plant Science
Publisher
Frontiers Media SA
Volume
16
Pages
1754679–1754679
Publication date
5 January 2026
Language
EN