Ant Colony Optimization Algorithm for Robot Path Planning

摘要

In this article two different optimization algorithms are presented to solve the deficiency of ant colony algorithm such as slow convergence rate and easy to fall into local optimum. This method based on Max-Min Ant System, established an adaptive model for pheromone evaporation coefficient adjusted adaptively and avoided the ants falling into local optimum. At the same time, this optimization algorithm used the strategy of the survival of the fittest way to optimize the pheromone update mechanism to accelerate the convergence rate. Finally, by comparison with ant colony algorithm, the simulation results show that, both the optimal path and routing time are optimized, and proved that the optimization algorithm is valid and feasible.