Intelligent Mine Truck Roadway Keeping Path Planning Method in Mapless Mode in Underground Mining Area

With the expanding application of autonomous driving technology in underground mining scenarios, the path planning of intelligent mining truck in underground roadway environments has become an important and complex task. In this paper, we propose an intelligent path planning method for mine trucks, specifically designed for underground mining areas where pre-existing maps are unavailable due to location data loss. The method can perform roadway keeping path planning even in the absence of prior map information. It uses a three-degree-of-freedom(Zoom Pan Rotate) rectangular search box to process road boundary data obtained through radar sensing. Meanwhile, this paper optimises the model based on the original algorithm for the special scenario of an underground mine tunnel. Simulation results show that the optimised algorithm has stronger robustness in the scenario of irregular boundaries of underground roadways, and the paths generated by the optimised algorithm are smoother than those generated by the road centreline algorithm and the basic algorithm, which can complete the path planning task under multiple working conditions.