Path Tracking Control of a Large Rear-Wheel–Steered Combine Harvester Using Feedforward PID and Look-Ahead Ackermann Algorithms

Shaocen Zhang, Qingshan Liu, Haihui Xu, Zhang Yang, Xinyu Hu, Qi Song () and Xinhua Wei
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Shaocen Zhang: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Qingshan Liu: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Haihui Xu: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Zhang Yang: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Xinyu Hu: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Qi Song: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Xinhua Wei: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China

Agriculture, 2025, vol. 15, issue 7, 1-23

Abstract: Autonomous driving solutions for agricultural machinery have advanced rapidly; however, large-wheeled harvesters present unique challenges compared to traditional vehicles. Specifically, the 5.4 m cutting width, 9.2 m minimum turning diameter, and rear-wheel–steered configuration demand specialized path tracking and steering methods. To address these challenges, this study developed an integrated system combining feedforward PID and Look-Ahead Ackermann (LAA) algorithms with sensors, actuators, and an embedded control platform. Field experiments indicated that the system maintained an average lateral deviation of approximately 5 cm on straight-line paths, with slightly larger errors observed only during turning or alignment maneuvers. Additionally, a “three-cut” steering method was implemented, which enhanced path tracking accuracy and prevented crop damage at headland turns. Successful field tests confirmed the robustness of the developed system, highlighting its practical potential for production-level autonomous harvesting.

Keywords: autonomous driving; combine harvester; feedforward PID algorithm; look-ahead Ackermann (LAA) algorithm; path tracking control (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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