Research Progress on Path Planning and Tracking Control Methods for Orchard Mobile Robots in Complex Scenarios

Yayun Shen, Yue Shen, Yafei Zhang, Chenwei Huo, Zhuofan Shen, Wei Su and Hui Liu ()
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Yayun Shen: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Yue Shen: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Yafei Zhang: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Chenwei Huo: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Zhuofan Shen: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Wei Su: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Hui Liu: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China

Agriculture, 2025, vol. 15, issue 18, 1-40

Abstract: Orchard mobile robots (OMR) represent a critical research focus in the field of modern intelligent agricultural equipment, offering the potential to significantly enhance operational efficiency through the integration of path planning and tracking control navigation methods. However, the inherent complexity of orchard environments presents substantial challenges for robotic systems. Researchers have extensively investigated the robustness of various path planning and tracking control techniques for OMR in complex scenes, aiming to improve the robots’ security, stability, efficiency, and adaptability. This paper provides a comprehensive review of the state-of-the-art path planning and tracking control strategies for OMR in such environments. First, it discusses the advances in both global and local path planning methods designed for OMR navigating through complex orchard scenes. Second, it examines tracking control approaches in the context of different motion models, with an emphasis on the application characteristics and current trends in various scene types. Finally, the paper highlights the technical challenges faced by OMR in autonomous tasks within these complex environments and emphasizes the need for further research into navigation technologies that integrate artificial intelligence with end-to-end control systems. This fusion is identified as a promising direction for achieving efficient autonomous operations in orchard environments.

Keywords: complex scenarios; orchard mobile robot; path planning; tracking control; research progress (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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