Path tracking control for brake-steering tracked vehicles based on an improved pure pursuit algorithm.

Path tracking is critical for agricultural vehicles to achieve autonomous operation and to improve operational efficiency and accuracy. This study aims to address the high-precision path tracking requirements for the tracked vehicle GY-8. An improved pure pursuit path tracking control method is proposed to enhance the performance of path tracking. For the GY-8 vehicle's single-sided braking and steering approach, a dual-wheel differential kinematic model is established. A smooth steering method using PWM (Pulse Width Modulation) is designed to reduce the likelihood of deviation from the predetermined path due to PWM braking steering. A method based on the theory of circular arc similarity is introduced to determine the path curvature and segmentation. The NSGA-II optimisation algorithm is employed to optimise and obtain the optimal look-ahead distance for different curvature segments, thereby enhancing the accuracy of path tracking. The improved algorithm was experimentally validated for path tracking on paved surfaces. In the experiments, the improved algorithm demonstrated average error, maximum error, error standard deviation, and Fréchet distance of 0.0266 m, 0.0973 m, 0.0195 m, and 0.0891 m, respectively. This represents a 15.6%, 25.8%, 4.9%, and 27.6% improvement over the pure tracking algorithm. When applying the improved pure tracking algorithm to path tracking in agricultural orchard soil environments, the results indicated maximum error, average error, and error standard deviation of 0.1272 m, 0.0351 m, and 0.0215 m, respectively. The overall findings suggest that the improved method significantly enhances the accuracy of path tracking, providing theoretical support for advancing navigation technology in tracked vehicles. • An improved path tracking control approach proposed. • Circular arc similarity method determines curvature of each path segment. • NSGA-II optimizes look-ahead distance for varying curvatures. • Experimental results show that the algorithm performs satisfactorily. [ABSTRACT FROM AUTHOR]