The obstacle avoidance path planning of flying robot for overhead power line inspection based on an improved A* algorithm

In order to ensure the safe and collision-free navigation of electric power inspection drones in dynamic environments while simultaneously achieving optimal global and local paths and minimizing planning time, this paper presents a novel approach for obstacle avoidance path planning. The proposed method is based on an enhanced version of the $A^{*}$ algorithm specifically tailored for electric power inspection drones. Firstly, the $\mathbf{A}^{*}$ algorithm model analyzes the number and positional information of obstacle grid cells to quantify the density of obstacles in the environment. Next, the obstacle density information is integrated into the search strategy of the A* algorithm by enhancing the evaluation function and optimizing the selection of child nodes. Finally, by designing a node optimization algorithm, bidirectional smoothing and optimization of the path can be achieved.