Research of path planning for mobile robot based on improved ant colony optimization algorithm
The paper proposes an improved ant colony optimization algorithm. This method first designs two fuzzy controllers to optimize three parameters α, β, ρ. Then it establishes a dynamic searching window for ants and chaos information are added when near-neighbour city table is constituted in order to increase research speed in initial stages of algorithm. In addition, the concept of active degree of city node is presented as future information to supervise ants to construct solution and update pheromone. Finally a new evaluation criterion is produced to distinguish where paths are excellent or not. So the strategy not only conquers the weakness of easily running into local optimization while making route optimization, but also enhances efficient convergence of ant colony optimization algorithm. Results of large numbers of computer simulations demonstrate that this novel algorithm can plan optimal path rapidly in intricate three dimension (3-D) environment.