Path planning of mine robot based on a novel heuristic algorithm with regular hexagon grids

In the traditional square grid map, when robot encounters an obstacle, it is easy to collide with the obstacle when moving along diagonal direction, has poor capability in obstacle-avoiding and stability, and time consumed in each step during real-time detection cannot be uniquely determined. In view of the above problems, based on working environment of regular hexagon grid, a path optimization method for multiple parallel mobile mine robots by using improved heuristic path search algorithm is proposed. In this paper, a comparative analysis of single robot in square and regular hexagon grid modeling environment is carried out from three aspects of obstacle-avoiding angle, obstacle-avoiding ability and optimal path. The results show that for a single robot, path length cost under regular hexagon grid map is less than that in square grid map, and from path planning of a single robot, regular hexagon grid map is more conducive to obtain the shortest path, so it is concluded that regular hexagon grid is more suitable for robot working environment modeling than traditional square grid. Aiming at path planning problem of parallel movement of multiple robots in collaborative operation, an improved heuristic path search algorithm is used to optimize path of multiple robots on the basis of working environment of regular hexagon grid:Multiple collaborative robot paths are planned by use of improved heuristic estimation function, which determines the one of all adjacent grids around the current robot location to be traversed by the robot. The improved heuristic estimation function is used to plan the path of multiple cooperative robots. According to the number of grids traversed by robot and deformed Manhattan distance between candidate grid and target grid of the robot, the heuristic estimation function can evaluate fitness value of adjacent grids. The simulation results show that total path length and running time of the algorithm are reduced by more than 10% compared with the square grid map, collision between the robot and static obstacles and among the robots is effectively avoided, and safety of the robot is improved. With increase of the number of robots, the improved heuristic path search algorithm has more obvious optimization effect on robot path and algorithm running time under the regular hexagon grid map.