An obstacle avoidance path planning method for mine cars with improved artificial potential field
In order to overcome the problem of too frequent path deviation in path planning caused by the traditional artificial potential field algorithm aiming at local optimal solutions,this paper proposed a dynamic obstacle avoidance path planning method based on the improved artificial potential field algorithm design.The method models the route and environment of the unmanned mining vehicle through the grid map method,and then forms a grid map connecting the start point and the target point.For the obstacle avoidance prob-lem,the gravitational potential field,repulsive potential field and integrated potential field model were established according to the char-acteristics of the path in the mining area;the artificial potential field function was improved in the model,and the area of the potential field was optimized to construct an integrated potential field model that strengthens the repulsive force at distant points.Considering that the mountain scene environment of the mine is relatively single,the improved algorithm restricts the search path by simulating the road through simulation experiments,so that the unmanned mine car searches for the best path in the established restricted space,and the simulation results show that the path planning algorithm can avoid the trajectory deviation and the local oscillations to a greater extent,and improves the travelling efficiency of the mine car.
improved artificial potential field algorithmunmannedroute planningsimulated road
万方数据
维普
