Enhanced ant Colony Optimization Algorithm for Global Path Planning of Mobile Robots

An enhanced ant colony optimization algorithm is proposed to plan global path of mobile robots under complicated environments.The path-locked phenomenon is avoided through modifying both initial environment pheromone and state transition probability.The determinant search based on interest area of viewpoint,combined with stochastic search,improves the roundabout of trajectory.Local pheromone diffusion mechanism is introduced to advance global optimization performance.The experimental results show that the new algorithm can provide desirable safety path under the complex situation which contains overly dense obstacles or many concave regions,and computational time can meet the requirement of particle applications.