Robot path planning based on random expansion of ant colony optimization

Abstract

Aimed at the shortcomings of the ant colony algorithm in robot path planning, which need much time and easy to fall in premature stagnation. This paper proposes a random expansion ant colony optimization algorithm through giving a possible way in the initial pheromone distribution to narrow the searching range of algorithm and raise the searching speed. At the same time random expansion factor is introduced to ant colony optimization algorithm, improved the diversity of routes and global optimization properties. The simulations result shows that the algorithm has excellent global optimization property and fast convergence speed. © 2012 Springer-Verlag GmbH.