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Agricultural Machinery Path Tracking with Varying Curvatures Based on an Improved Pure-Pursuit Method

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  • 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 311300, China)

  • 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 311300, 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 311300, 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 311300, 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 311300, 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 311300, China)

Abstract

The current research on path tracking primarily focuses on improving control algorithms, such as adaptive and predictive models, to enhance tracking accuracy and stability. To address the issue of low tracking accuracy caused by variable-curvature paths in automatic navigation within agricultural environments, this study proposes a fuzzy control-based path-tracking method. Firstly, a pure-pursuit model and a kinematic model were established based on a Four-Wheel Independent Steering and Four-Wheel Independent Driving (4WIS-4WID) structure. Secondly, a fuzzy controller with three inputs and one output was designed, using the lateral deviation, d e ; heading deviation, θ e ; and bending degree, c , of the look-ahead path as the input variables. Through multiple simulations and adjustments, 75 control rules were developed. The look-ahead distance, Ld , was obtained through fuzzification, fuzzy inference, and defuzzification processes. Next, a speed-control function was constructed based on the agricultural machinery’s pose deviations and the bending degree of the look-ahead path to achieve variable speed control. Finally, field tests were conducted to verify the effectiveness of the proposed path-tracking method. The tracking experiment results for the two types of paths indicate that under the variable-speed dynamic look-ahead distance strategy, the average lateral deviations for the variable-curvature paths were 1.8 cm and 3.3 cm while the maximum lateral deviations were 10.1 cm and 10.5 cm, respectively. Compared to the constant-speed fixed look-ahead pure-pursuit model, the average lateral deviation was reduced by 56.1% and the maximum lateral deviation by 50.4% on the U-shaped path. On the S-shaped path, the average lateral deviation was reduced by 56.0% and the maximum lateral deviation by 58.9%. The proposed method effectively improves the path-tracking accuracy of agricultural machinery on variable-curvature paths, meeting the production requirements for curved operations in agricultural environments.

Suggested Citation

  • Jiawei Zhou & Junhao Wen & Liwen Yao & Zidong Yang & Lijun Xu & Lijian Yao, 2025. "Agricultural Machinery Path Tracking with Varying Curvatures Based on an Improved Pure-Pursuit Method," Agriculture, MDPI, vol. 15(3), pages 1-18, January.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:3:p:266-:d:1577490
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    References listed on IDEAS

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    1. Haoling Ren & Jiangdong Wu & Tianliang Lin & Yu Yao & Chang Liu, 2023. "Research on an Intelligent Agricultural Machinery Unmanned Driving System," Agriculture, MDPI, vol. 13(10), pages 1-19, September.
    2. Haoling Ren & Jiangdong Wu & Tianliang Lin & Yu Yao & Chang Liu, 2023. "Correction: Ren et al. Research on an Intelligent Agricultural Machinery Unmanned Driving System. Agriculture 2023, 13 , 1907," Agriculture, MDPI, vol. 14(1), pages 1-8, December.
    3. Wei Liu & Jinhao Zhou & Yutong Liu & Tengfei Zhang & Meng Yan & Ji Chen & Chunjian Zhou & Jianping Hu & Xinxin Chen, 2024. "An Ultrasonic Ridge-Tracking Method Based on Limiter Sliding Window Filter and Fuzzy Pure Pursuit Control for Ridge Transplanter," Agriculture, MDPI, vol. 14(10), pages 1-25, September.
    4. Zejin Chen & Haifeng Wang & Mengchuang Zhou & Jun Zhu & Jiahui Chen & Bin Li, 2024. "Design and Experiment of an Autonomous Navigation System for a Cattle Barn Feed-Pushing Robot Based on UWB Positioning," Agriculture, MDPI, vol. 14(5), pages 1-17, April.
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    Cited by:

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    2. Huanyu Liu & Zhihang Han & Junwei Bao & Jiahao Luo & Hao Yu & Shuang Wang & Xiangnan Liu, 2025. "Intelligent Path Tracking for Single-Track Agricultural Machinery Based on Variable Universe Fuzzy Control and PSO-SVR Steering Compensation," Agriculture, MDPI, vol. 15(11), pages 1-28, May.
    3. Liwei Zhu & Weiming Sun & Qian Zhang & En Lu & Jialin Xue & Guohui Sha, 2025. "Tractor Path Tracking Control Method Based on Prescribed Performance and Sliding Mode Control," Agriculture, MDPI, vol. 15(15), pages 1-16, August.
    4. Seulgi Choi & Xiongzhe Han & Eunha Chang & Haetnim Jeong, 2025. "LiDAR-IMU Sensor Fusion-Based SLAM for Enhanced Autonomous Navigation in Orchards," Agriculture, MDPI, vol. 15(17), pages 1-25, September.

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