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September 10, 2025Journal of Field Robotics

Advances in Path‐Planning Algorithms for Agricultural Robots

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Authors

YGYanpeng GaoGuangdong University of TechnologyQJQuan JiangHenry Ford Health SystemMWMing WangAnhui Agricultural University

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Overview

Analysis of path planning strategies enhances autonomous navigation in agricultural robots, indicating future integration of AI technologies.

Key Points

  • Path planning algorithms demonstrate varying strengths in precision and operational efficiency across diverse agricultural environments.
  • Traditional classical algorithms deliver high stability but lack adaptability compared to modern intelligent bionic algorithms.
  • Sampling-based planning excels in obstacle avoidance, while machine learning algorithms enable adaptive decision-making based on data-driven insights.
  • Integrating multiple algorithm strengths with AI and cloud computing may enhance future path planning in agriculture.

Cite This Study

Gao et al. (2025) studied this question.

synapsesocial.com/papers/68c1a27254b1d3bfb60dde7ehttps://doi.org/10.1002/rob.70023
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