## 1 Introduction  
With the development of unmanned technology, it has been widely applied in the fields of unmanned vehicles and drones. The working environment underground is harsh, with frequent safety accidents, and mine areas usually operate 24 h a day. Drivers need to overcome their own fatigue, making driving work boring and posing certain safety hazards [1]. Underground scenes have advantages such as relatively simple, closed roads, low traffic volume, fewer people, and low-speed environments compared to urban road scenes. Therefore, the most urgent need for developing autonomous driving technology is in the underground scene. At present, some scholars have conducted theoretical research on unmanned driving technology for underground mine vehicles. In [2], the modeling and validation of the operation process control of underground unmanned locomotives are researched. In [3], a feasibility study on the unmanned driving of underground explosion-proof vehicles in coal mines based on 4G communication technology has been carried out. In [4], the perception, decision-making, and control of unmanned vehicles in tunnel environments are researched, and the safe and reliable control of underground unmanned trackless rubber-wheeled vehicles is achieved. Autonomous driving technology provides an important means to achieve the safe, efficient, and intelligent transportation of mine vehicles. It can replace manual labor, improve transportation efficiency, reduce costs, and minimize safety risks. However, the development bottleneck of underground unmanned driving technology is mainly manifested in the following: (1) There is no global positioning system (GPS) signal on the underground roadway, and vehicles cannot realize positioning. (2) The length of underground tunnels is usually more than ten kilometers, and there are multiple corners and forks, so it is difficult to construct large-scale high-precision maps. (3) There are other vehicles in the tunnels, which necessitates a highly accurate vehicle path planning and obstacle avoidance ability. These issues have led to the slow development of underground unmanned vehicles. Therefore, this paper focuses on the path planning problem of underground unmanned mine vehicles to achieve unmanned vehicle navigation, which has significant application prospects and practical significance for liberating workers, reducing costs, and improving the efficiency of the entire transportation system [5]. At present, most scholars have conducted research on urban road vehicles, and there is relatively little research on path-planning methods for underground mine vehicles. In order to improve the transportation efficiency of underground unmanned mine vehicles, this paper proposes a path-planning method suitable for the structure of mine tunnels. The easily implementable A* algorithm is used as the global planning method and the efficient DWA algorithm is used as the local planning method. The reliability and adaptability of the algorithm are improved through optimization and improvement to achieve path planning for underground unmanned mine vehicles. The main contributions are as follows:  
1. The logarithmic function is introduced to improve the heuristic function coefficient. The adaptive adjustment of the A* algorithm is realized, and the key node selection strategy and 3 times Clamped-B spline are used to optimize and smooth the global path. 2. A DWA fuzzy controller based on the fuzzy control principle is proposed and designed, which adjusts the coefficient weight of the DWA evaluation function in real-time by judging the distance between the vehicle, obstacles, and target points. 3. A hybrid path planning method based on the improved A* algorithm and the fuzzy control DWA algorithm is proposed, and the global path key points are used as the local target points of the DWA to guide the vehicle and perform dynamic obstacle avoidance. The remaining sections of this paper are organized as follows. In the second section, the related works on the path-planning methods are briefly reviewed.