Improved ant colony algorithm for path planning based on location and energy consumption inspiration
In order to solve the problems of poor comprehensive optimization ability,slow convergence speed,and weak algorithm robustness in the application of classic ant colony algorithm in mobile robot path planning,a modified ant colony optimization algorithm based on location and energy consumption heuristic is proposed.Considering the robot's travel path length,travel path slope,and energy consumption caused by turning,a comprehensive energy consumption heuristic factor is proposed.Considering that between the starting point and the end point of path,straight-line distance is the shortest a straight-line distance heuristic factor is proposed to guide the ants to approach the path around the straight from starting point to the end point.A distance heuristic factor to the end point is proposed to guide the ants to move towards the target point.A heuristic function combining three heuristic factors is designed to optimize mode of the state transition calculation.In addition,by introducing dynamic pheromone evaporation factor,improving pheromone increment,and designing pheromone constraints,the pheromone update strategy is optimized.Comparative analysis of multiple simulated experiments in various environments shows that the improved algorithm has more excellent show in optimizing path length,path height variance,and comprehensive performance.
ant colony optimization algorithmpath planningenergy consumption heuristic factormobile robot
万方数据
维普
