Author(s)

Jingang Cao

Department of Computer, North China Electric Power University, Baoding, China.

Aiming at the disadvantages of the basic ant colony algorithm, this paper proposes an improved ant colony algorithm for robot global path planning. First, adjust the pheromone evaporation rate dynamically to enhance the global search ability and convergence speed, and then modify the heuristic function to improve the state transition probabilities in order to find the optimal solution as quickly as possible; and finally change the pheromone update strategy to avoid premature by strengthening pheromone on the optimal path and limiting pheromone level. Simulation results verify the effectiveness of the improved algorithm.

Path Planning, Ant Colony Algorithm, Grid Method

Cao, J. (2016) Robot Global Path Planning Based on an Improved Ant Colony Algorithm. Journal of Computer and Communications, 4, 11-19. doi: 10.4236/jcc.2016.42002.