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

Huanyu Liu1, Zhihang Han1, Jiaqin Yin1

  • 1Institute of Modern Agricultural Equipment, Xihua University, Chengdu, China.

Frontiers in Plant Science
|January 21, 2026
PubMed
Summary

Tracked agricultural vehicles can now navigate complex terrain more accurately using a new slip-aware control method. This approach significantly reduces path-tracking errors caused by track slip, enhancing stability and operational efficiency.

Keywords:
extended Kalman filterimproved particle swarm optimizationpure pursuit algorithmslip compensationtracked agricultural machinery

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Area of Science:

  • Agricultural Engineering
  • Robotics
  • Control Systems

Background:

  • Tracked agricultural vehicles face challenges with track slip, impacting path-tracking accuracy and stability in complex farmland.
  • Conventional geometric tracking algorithms struggle under slip conditions, necessitating advanced control strategies.

Purpose of the Study:

  • To propose a novel slip-aware look-ahead point offset path-tracking control method for tracked agricultural machinery.
  • To enhance path-tracking accuracy and motion stability in the presence of track slip.

Main Methods:

  • An extended Kalman filter (EKF) fuses RTK-IMU and wheel-speed data for real-time slip ratio estimation.
  • A slip-aware target-point offset mechanism optimizes control using an improved particle swarm optimization (PSO) algorithm.
  • A fuzzy controller adaptively adjusts look-ahead distance, and a low-pass filter smooths velocities.

Main Results:

  • Simulations and field experiments demonstrate significant reductions in lateral tracking errors under severe slip conditions.
  • Field tests showed maximum lateral deviation reduced by up to 78.1% and average deviation by 50.6% compared to traditional methods.
  • The method ensures smooth trajectories and improved robustness on soft, high-slip terrain.

Conclusions:

  • The proposed slip-aware control method effectively enhances path-tracking accuracy and robustness for tracked agricultural vehicles.
  • This lightweight control framework offers a practical solution for autonomous navigation in complex agricultural environments.
  • The approach is suitable for autonomous navigation and plant-protection operations, improving overall efficiency.