Research on Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm
Aiming at the problems of the traditional ant colony algorithm,such as high iteration times,long planning paths,and redundant inflection points,an improved ant colony algorithm is proposed.Firstly,the angle factor is introduced into the heuristic function,and the importance degree of local influence factor,global influence factor and angle influence factor are characterised by local influence coefficient,global influence coefficient and angle influence coefficient.At the same time,the pheromone volatility coefficient and the information heuristic factor are improved to enhance the guiding effect of the pheromone.Secondly,in order to make the algorithm more directive during the initial search,the pheromone concentration matrix is initialised according to the known information of the map and the optimized path features.Finally,the improved algorithm is used to plan the path for secondary opti-mization,reducing the length of the path and the number of turns to reduce the path length and the number of turns.To verify the effectiveness of the algorithm,Matlab is used to simulate the improved algorithm in the raster map,and the results show that the im-proved algorithm can obtain the optimal path with shorter length and fewer turns with fewer iterations.
ant colony algorithmangle factorpheromone guidancepheromone concentration matrixsecondary optimization
万方数据
维普
