Study on an Optimal Path Planning for a Robot Based on an Improved ANT Colony Algorithm

Abstract

To solve the path planning problems of rescuing and coal exploring robot in three-dimensional space environment, a path planning method of rescuing and coal exploring robot based on the improved ant colony algorithm was proposed. Firstly, a three-dimensional model was built with the mountainous elevation data and grid method. Furthermore, on the basis of the traditional ant colony algorithm, node transition probability, node selection way and pheromone update method were respectively optimized and improved through introducing a new heuristic function factor, node random selection mechanism and update strategy of pheromone that includes the local updating and global updating of pheromone. Finally, the feasibility and effectiveness of ant colony algorithm was simulated and tested with MATLAB software. The simulation results showed that the traditional ant colony algorithm and improved ant colony algorithm both could search out a security optimal path for rescuing & coal exploring robot in three dimensional space environment. Under the different task requirements, comparing with the traditional ant colony algorithm, the improved ant colony algorithm could effectively shorten the searching path length and reduce the path searching time. Moreover, the improved ant colony algorithm also showed a greater decision-making ability and better convergence performance. The simulation results indicated the improved ant colony algorithm should be correct, feasible and effective.