Abstract
Ant colony algorithm is easy to fall into local optimum and its convergent speed is slow in solving mobile robot path planning. Therefore, an ant colony algorithm based on angle guided is proposed in this paper to solve the problems. In the choice of nodes, integrate the angle factor into the heuristic information of the ant colony algorithm to guide the ants' search direction and improve the search efficiency. The pheromone differential updating is carried out for different quality paths and the pheromone chaotic disturbance updating mechanism is introduced, then the algorithm can make full use of the better path information and maintain a better global search ability. According to simulations, its global search is strong and it can range out of local optimum and it is fast convergence to the global optimum. The improved algorithm is feasible and effective.
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