数字农科院2.0

Application of Navigation Path Planning and Trajectory Tracking Control Methods for Agricultural Robots

文献类型： 外文期刊

作者： Ye, Fan;Le, Feixiang;Cui, Longfei;Han, Shaobo;Gao, Jingxing;Qu, Junzhe;Xue, Xinyu

作者机构：

关键词： agricultural robots;autonomous navigation;path planning;trajectory tracking;control methods;multi-robot coordination;obstacle avoidance technology

期刊名称： AGRICULTURE-BASEL

ISSN：

年卷期： 2025 年 16 卷 1 期

页码：

收录情况： SCIE（2025版）

摘要： Autonomous navigation is a core enabler of smart agriculture, where path planning and trajectory tracking control play essential roles in achieving efficient and precise operations. Path planning determines operational efficiency and coverage completeness, while trajectory tracking directly affects task accuracy and system robustness. This paper presents a systematic review of agricultural robot navigation research published between 2020 and 2025, based on literature retrieved from major databases including Web of Science and EI Compendex (ultimately including 95 papers). Research advances in global planning (coverage and point-to-point), local planning (obstacle avoidance and replanning), multi-robot cooperative planning, and classical, advanced, and learning-based trajectory tracking control methods are comprehensively summarized. Particular attention is given to their application and limitations in typical agricultural scenarios such as open-fields, orchards, greenhouses, and hilly slopes. Despite notable progress, key challenges remain, including limited algorithm comparability, weak cross-scenario generalization, and insufficient long-term validation. To address these issues, a scenario-driven scenario-constraint-performance adaptive framework is proposed to systematically align navigation methods with environmental and operational conditions, providing practical guidance for developing scalable and engineering-ready agricultural robot navigation systems.

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