Path optimization for Automatic Guided Vehicle Based on fusion algorithm of particle swarm and ant colony

摘要

Aim at search precocity of particle swarm algorithm and slow convergence speed problem for ant colony algorithm, in the automatic guided vehicle path optimization a path optimization algorithm is proposed, which is fused by particle swarm algorithm and ant colony algorithm. Firstly, robot motion space model of the algorithm is created using link figure. After got fixed circulation rapid global, search to get more optimal path by means of improved fastest convergence ant system, then using a particle ants information communication method to update pheromone, finally, optimal path is drew. The simulation experiment shows that, even in the complex environment, this algorithm can also has the advantage of ant colony algorithm to optimize the result accurately and particle swarm algorithm local optimization accurately and rapidly, and a global security obstacle avoidance of optimal path is plot, the route is shorten 8% compare than the general ant colony algorithm.