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Path Tracking Control of Agricultural Automatic Navigation Vehicles Based on an Improved Sparrow Search-Pure Pursuit Algorithm

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  • Junhao Wen

    (College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
    National Engineering Technology Research Center of State Forestry and Grassland Administration on Forestry and Grassland Machinery for Hilly and Mountainous Areas, Hangzhou 311300, China
    Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in South-Eastern China (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

  • Liwen Yao

    (College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
    National Engineering Technology Research Center of State Forestry and Grassland Administration on Forestry and Grassland Machinery for Hilly and Mountainous Areas, Hangzhou 311300, China
    Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in South-Eastern China (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

  • Jiawei Zhou

    (College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
    National Engineering Technology Research Center of State Forestry and Grassland Administration on Forestry and Grassland Machinery for Hilly and Mountainous Areas, Hangzhou 311300, China
    Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in South-Eastern China (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

  • Zidong Yang

    (College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
    National Engineering Technology Research Center of State Forestry and Grassland Administration on Forestry and Grassland Machinery for Hilly and Mountainous Areas, Hangzhou 311300, China
    Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in South-Eastern China (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

  • Lijun Xu

    (College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
    National Engineering Technology Research Center of State Forestry and Grassland Administration on Forestry and Grassland Machinery for Hilly and Mountainous Areas, Hangzhou 311300, China
    Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in South-Eastern China (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

  • Lijian Yao

    (College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
    National Engineering Technology Research Center of State Forestry and Grassland Administration on Forestry and Grassland Machinery for Hilly and Mountainous Areas, Hangzhou 311300, China
    Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in South-Eastern China (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

Abstract

A pure pursuit method based on an improved sparrow search algorithm is proposed to address low path-tracking accuracy of intelligent agricultural machinery in complex farmland environments. Firstly, we construct a function relating speed to look-ahead distance and develop a fitness function based on the prototype’s speed and pose deviation. Subsequently, an improved sparrow search algorithm (ISSA) is employed to adjust the pure pursuit model’s speed and look-ahead distance dynamically. Finally, improvements are made to the initialization of the original algorithm and the position update method between different populations. Simulation results indicate that the improved sparrow search algorithm exhibits faster convergence speed and better capability to escape local extrema. The real vehicle test results show that the proposed algorithm achieves an average lateral deviation of approximately 3 cm, an average heading deviation below 5°, an average stabilization distance under 5 m, and an average navigation time of around 46 s during path tracking. These results represent reductions of 51.25%, 30.62%, 49.41%, and 10.67%, respectively, compared to the traditional pure pursuit model. Compared to the pure pursuit model that only dynamically adjusts the look-ahead distance, the proposed algorithm shows reductions of 34.11%, 24.96%, 32.13%, and 11.23%, respectively. These metrics demonstrate significant improvements in path-tracking accuracy, pose correction speed, and path-tracking efficiency, indicating that the proposed algorithm can serve as a valuable reference for path-tracking research in complex agricultural environments.

Suggested Citation

  • Junhao Wen & Liwen Yao & Jiawei Zhou & Zidong Yang & Lijun Xu & Lijian Yao, 2025. "Path Tracking Control of Agricultural Automatic Navigation Vehicles Based on an Improved Sparrow Search-Pure Pursuit Algorithm," Agriculture, MDPI, vol. 15(11), pages 1-23, June.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:11:p:1215-:d:1670102
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    References listed on IDEAS

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    1. Jiao, Bin & Lian, Zhigang & Gu, Xingsheng, 2008. "A dynamic inertia weight particle swarm optimization algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 37(3), pages 698-705.
    2. Jiankai Xue & Bo Shen, 2024. "A survey on sparrow search algorithms and their applications," International Journal of Systems Science, Taylor & Francis Journals, vol. 55(4), pages 814-832, March.
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