Rescue Path Planning and Simulation Analysis of Mining Robot Based on Improved A* Algorithm

Abstract

Purposes The situation of post-disaster site of coal mine underground is complex. Aiming at the fact that traditional A* algorithm-based coal mine robot rescue path planning bears path insecurity, low efficiency, and other problems, and by combining with the raster map and the characteristics that the rescue robot can move along any direction, multi-faceted improvement of the traditional A* algorithm is realized. Methods First, the concept of robot size superimposed to obstacles is introduced to ensure the safety of the path. Second, the computational complexity is reduced by optimising the heuristic function to reduce the number of extensions that deviate from the optimal path nodes, and to reduce the redundant nodes and path transitions. Finally, a dynamic adjustment algorithm is used to round the corners of path turns, and the resulting path is smoothed to improve the operability of path. The optimised path with smaller path cost, shorter time consumption, and fewer turns is finally obtained. Based on the improved A* algorithm, the simulation test of rescue robot path planning under different sizes and different obstacle coverages is carried out by using MATLAB. Findings Compared with the traditional A* algorithm, the improved A* algorithm in rugged environment maps reduces the searching nodes by 26.51%, the computation time by 80.42%, the path length by 31.85%, and the number of turns by 44.44%, which improves the search efficiency and smoothness of the path. Conclusions The improved A* algorithm provides a theoretical basis for the rescue work of coal mine robots under complex working conditions.

Keywords

• a* algorithm optimization
• coal mine rescue robot
• path planning
• heuristic functions
• dynamically adjustment algorithm