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A Chaotic Ant Colony System for Path Planning of Mobile Robot

Aiming at the path planning problem of mobile robot, a chaotic ant colony system was presented. The idea of the algorithm was that first generated chaotic sequences as the initial pheromone matrix and then ant colony traversed grids environment once, pheromone on the path was updated, as the completeness of the pheromone initialization. Pheromone update strategy adopt self-adaptive chaotic disturbance to avoid the search being trapped in local optimum. Grids environment simulated the robot workspace. Through the process of self-organization and chaos, the ant colony found the optimal path in the robot’s static environment. Simulation results show that chaotic ant colony system not only enhances the global search capability, but also more effective than the traditional ACS, moreover, it’s a novel approach to the robot path planning.