Abstract: To improve the efficiency of path planning and avoid ant colony algorithm outputting non optimal paths, a multi-agent path planning model is proposed. The grid method is used to establish the environment awareness model of agents, improving the local and global pheromone update rules in the ant colony algorithm, and constraining the ants to travel by adjusting the number of turns and pheromone concentration. The algorithm can intelligently enlarge or reduce the pheromone concentration in the path. When the number of iterations reaches the set maximum, the output value is the optimal path planning result. Experimental results have shown that the improved algorithm achieves shorter planning paths and faster iterative convergence speed.

Key words: improve ant colony algorithm, multi agent, grid method, environmental perception, pheromone update