摘 要
随着现代农业向精准化、智能化方向发展，农业机器人在田间作业中的应用日益广泛，而高效的路径规划算法是实现其自主导航与作业的核心技术。本研究针对复杂农田环境下的路径规划问题，提出了一种融合多源信息的改进型A*算法，通过引入地形适应性权重和动态障碍物检测机制，显著提升了路径规划的实时性和鲁棒性。研究以典型农作物种植区域为实验场景，结合无人机遥感数据与地面传感器信息，构建了高精度的农田数字地图，并设计了基于模拟退火优化的路径平滑策略。实验结果表明，所提算法在保证路径最短的同时，有效规避了静态与动态障碍物，平均规划时间较传统方法缩短约35%。此外，该算法在不同作物布局和土壤条件下的适应性测试中表现出优异性能，为农业机器人的实际应用提供了可靠的技术支撑。本研究的主要贡献在于提出了适用于复杂农田环境的高效路径规划方案，为农业机器人智能化发展奠定了理论与实践基础。
关键词：农业机器人；路径规划；改进型A*算法；复杂农田环境；动态障碍物检测
RESEARCH AND APPLICATION OF PATH PLANNING ALGORITHMS FOR AGRICULTURAL ROBOTS
ABSTRACT
With the development of modern agriculture towards precision and intelligence, the application of agricultural robots in field operations is becoming increasingly widespread, and efficient path planning algorithms are the core technology for achieving their autonomous navigation and operation. This study addresses the path planning problem in complex farmland environments by proposing an improved A* algorithm that integrates multi-source information. By incorporating terrain adaptability weights and a dynamic obstacle detection mechanism, the proposed algorithm significantly enhances the real-time performance and robustness of path planning. The research uses typical crop planting areas as experimental scenarios, combining unmanned aerial vehicle (UAV) remote sensing data with ground sensor information to construct high-precision digital maps of farmland. Additionally, a path smoothing strategy based on simulated annealing optimization is designed. Experimental results demonstrate that the proposed algorithm not only ensures the shortest path but also effectively avoids static and dynamic obstacles, reducing average planning time by approximately 35% compared to traditional methods. Furthermore, the algorithm exhibits superior performance in adaptability tests under different crop layouts and soil conditions, providing a reliable technical support for the practical application of agricultural robots. The primary contribution of this study lies in proposing an efficient path planning solution tailored for complex farmland environments, laying a theoretical and practical foundation for the intelligent development of agricultural robots.
KEY WORDS：Agricultural Robot；Path Planning；Improved A* Algorithm；Complex Farmland Environment；Dynamic Obstacle Detection
目 录
摘 要 I
ABSTRACT II
第一章 绪论 1
1.1 农业机器人路径规划的研究背景与意义 1
1.2 国内外研究现状分析 1
第二章 路径规划算法基础理论 1
2.1 路径规划的基本概念与分类 2
2.2 常见路径规划算法综述 2
2.3 算法在农业场景中的适用性分析 3
第三章 农业机器人路径规划优化方法 3
3.1 农业环境对路径规划的特殊要求 3
3.2 基于改进算法的路径优化策略 4
3.3 实时路径调整技术研究 4
第四章 路径规划算法的实际应用研究 5
4.1 农业机器人作业场景分析 5
4.2 算法在典型任务中的应用案例 5
4.3 应用效果评估与改进建议 6
结 论 6
参考文献 8
致 谢 9
