Improved artificial potential field based ant colony optimization for path planning

Path planning field for mobile robot is an important problem that involves finding free path from initial position to goal position .in this paper we introduce an improved artificial potential field based on ant colony optimization .which can obtain additional attractive force to prevent artificial potential field from local minimum .and use ant colony optimization to determine the location of goal in the environment .we develop ant colony optimization to optimize planned path .we do not use the pheromone in all the path from initial position to goal position. We use pheromone in the goal position only. After that the proposed algorithm applied in a laptop computing equipped with 1.80GHz Intel core CPU, 2.5GB memory with 2014 MATLAB in Windows 8.1 Operating System. The simulation results confirm that the proposed algorithm could always find shortest path in less time. the comparison between ant colony optimization and genetic algorithm was also made in this paper.

Keywords:

path planning , ant colony optimization , artificial potential field