Research on Path Planning Based on Improved Ant Colony Algorithm
In view of the problems of low global search efficiency,easy to fall into local optima,and unreasonable local paths in traditional ant colony algorithms,this paper proposes a fusion of artificial potential field and ant colony path planning algorithm.This algorithm enhances the guidance effect of the target direction by introducing the artificial potential field target direction factor,thereby improving the search efficiency.At the same time,this algorithm improves the information pheromone update strategy,considering both the quality and length of the path,to obtain better solutions.Finally,this algorithm uses the triangle pruning method to smooth the planned path,improving the stability and safety of the robot's operation.Simulation and experimental results show that in the same map,the improved algorithm in this paper reduces the path length by 9.74%compared to the traditional algorithm.In terms of running time,it is shortened by 10.71%compared to the traditional algorithm.The conclusion shows that the proposed algorithm in this paper reduces the turning points in the overall path,shortens the walking path and time,improves the search efficiency,and is more in line with the actual operation and requirements of robots.
万方数据
维普
