Research on path planning of robot based on improved ant colony algorithm

Abstract

The basic ant colony algorithm applied to robot path planning in the two-dimensional static environment has problems of long search time, inefficiency and easy to fall into local optimization and so on. It makes improvements on the algorithm for these problems. It uses different expectation mechanism, updates the pheromone by taking evaporation coefficient adaptive approach, and joins the inflection point parameter as one evaluation criteria of the path. Simulation of the two algorithms shows the improved ant colony algorithm is stronger of searching ability and more efficient than the basic ant colony algorithm and gets a shorter path. The results show that the improved algorithm improves the efficiency of the algorithm and inhibits algorithm into local optimum and achieves search of robot's optimal path. Robot can avoid obstacles to reach the target point safely and quickly.