ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Sustainable and Intelligent Phytoprotection
This article is part of the Research TopicInnovative Techniques for Precision Agriculture and Big DataView all 18 articles
Dynamics Simulation and Autonomous Driving Algorithm Integration of Unmanned Harvester Based on TruckSim/Simulink
Provisionally accepted
- Zhejiang Sci-Tech University, Hangzhou, China
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To enhance the path tracking accuracy and dynamic adaptability of small unmanned harvesters in complex farmland environments, this paper proposes a simulation and autonomous driving algorithm framework based on TruckSim and Simulink. By innovatively integrating TruckSim's high-precision dynamic simulation with Simulink's powerful algorithm development capabilities, we have constructed a comprehensive simulation platform that accurately models the harvester's behavior in agricultural settings. This platform not only accurately simulates dynamic responses under various operating conditions but also facilitates efficient testing and validation of autonomous driving algorithms, thereby significantly shortening development cycles and lowering field-testing costs.For path planning, we implement a hybrid A* algorithm with dual heuristic search strategy to generate optimal paths in typical static agricultural operations. At the control level, a PID controller is designed to optimize path tracking and speed control performance. Furthermore, an Extended Kalman Filter-based road adhesion coefficient identification method is introduced, which integrates multi-sensor data to dynamically estimate road conditions and adjust control strategies accordingly. To enhance system robustness, a PID-based lane-keeping algorithm with steering-speed coordination mechanism is incorporated, significantly improving operational stability in various farmland environments. Field validation results demonstrate that this research provides an innovative simulation tool and effective algorithm validation platform, advancing the development of intelligent agricultural equipment.
Keywords: Agricultural scenes, Dual heuristic search, EKF, Hybrid A*, Intelligentagricultural equipment, Lane keeping, PID control
Received: 26 Nov 2025; Accepted: 02 Feb 2026.
Copyright: © 2026 Sun, Wang, Kong, Feng, Xu and Yu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Tao Xu
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