Autonomous walking path planning of underground handling robot based on improved A* and DWA algorithm

In view of the problems of many labors and low efficiency in the underground handling process, as well as the difficulties of many transport links, difficult transport operation and slow manual transport, the handling robot is taken as the research object, and the path planning method of underground roadway is studied through simulation and experiment. Firstly, the specific demand analysis of the underground transport conditions is carried out to determine the typical transportation scenarios such as “multi-transport point roadway” and “last 1km direct transport”, and the autonomous walking strategies are established respectively to improve the applicability and rationality of the autonomous walking path planning of the underground handling robot. Secondly, the path planning system scheme is designed, and the performance of the conventional path planning algorithms is compared and analyzed. The A* algorithm and the DWA algorithm are selected as the basic algorithms for global path planning and local path planning of the underground handling robot. Then, in order to solve the problem of low search efficiency and insufficient smoothness of the planned path of the conventional A* algorithm, the exponential optimization method and the quadratic B-spline curve method are used to improve the algorithm in turn, and the performance of the improved A* algorithm is compared and analyzed. The simulation results show that the improved A* algorithm shortens the path planning time of typical underground handling scenarios such as “the last 1 km direct transport” and “multi-transport point autonomous walking” by 24.62% and 22.02% respectively, and the path planning efficiency is improved, and the smoothness of the generated path is better. Besides, aiming at the problem that the traditional DWA algorithm has poor running time and path length, the predictive path evaluation function is constructed by coordinating the constraints of underground roadway speed limit, mobile chassis drive motor limit and handling robot braking distance limit, and the obstacle evaluation sub-function is introduced to improve the DWA algorithm by measuring safety and efficiency. The simulation results show that the planned path length and autonomous walking time based on the improved DWA algorithm are shortened by 31.27% and 42.33% respectively, which effectively improves the dynamic obstacle avoidance ability and path planning performance of the handling robot. Finally, the experimental roadway scenario and the handling robot model are built to carry out the path planning experiment of the underground handling robot. The experimental results show that the path planning efficiency of the improved A*-DWA fusion algorithm in the multi-transport point roadway autonomous walking A→B, A→C, the last 1 km direct transport and other scenarios is improved by 21.90%, 18.57% and 14.67%, respectively. The driving process realizes real-time and effective dynamic obstacle avoidance, and the planned path is safe, efficient and smooth, which can conform to the goal orientation of “reducing people, improving efficiency and increasing safety” and meet the needs of autonomous walking path planning of handling robots.