A path planning method for plant protection UAVs based on the fusion of dynamic weight functions and Bzier curves

Aiming at the problems of traditional path planning algorithms, such as high computational complexity, low search efficiency, and poor smoothness of planned paths due to non-compliance with kinematic constraints, this paper proposes a path planning method for plant protection Unmanned Aerial Vehicles (UAVs) based on the fusion of dynamic weight functions and Bzier curves. Firstly, the overall framework of the path planning algorithm is constructed based on the A* algorithm, and a weight function dynamically adjusted with the path is introduced to improve the heuristic function of the A* algorithm, which effectively reduces the number of search nodes and improves the overall search efficiency. Subsequently, the second-order Bzier curve is fused with the improved A* algorithm to reduce the number of turning points in the path planning process of the A* algorithm and improve the smoothness of the path. Finally, the effectiveness of the algorithm is verified based on Python and MATLAB platforms. The research results show that compared with the traditional A* algorithm, the improved A* algorithm fused with the dynamic weight function and Bzier curve can significantly improve the search efficiency and path smoothness; moreover, although the search efficiency of the search algorithm using dynamic weight coefficients is similar to that of the traditional algorithm, its path planning quality is significantly improved.