Downhole robot path planning based on improved D* algorithmn

In order to address the possible problems of the traditional D* algorithm in the path planning process, such as the proximity to obstacles, this paper improves both the distance function and the selection of child nodes. Firstly, the traditional D* algorithm using Euclid distances was improved to Manhattan distances that are more suitable for the special environment in the mine, thus reducing the cost of computing time. Then, improve the selection of child nodes, increase the danger factor as the node attribute, and exclude the node whose danger factor is 1, thereby increasing the safety distance of the planned route and reducing the number of search points in the path planning process. The experimental results show that for the downhole roadway environment simulation map, the calculation efficiency of the method is significantly improved and the planned path is safer and reasonable.