Path Planning for Mine Rescue Robots Based on Improved Ant Colony Algorithm

Abstract

An improved ant colony algorithm is proposed in order to improve the convergence speed and search efficiency of the traditional ant colony algorithm, as well as to reduce the influence of redundant fold points on the robot's movement mode. A 16-directional 24-neighbourhood ant search approach is adopted to expand the ant search range; the initial pheromone differential distribution is adopted to avoid the blindness of early search and improve the search efficiency of early ants; an obstacle avoidance strategy is introduced to greatly reduce the probability of ant deadlock, and a search direction angle is introduced to improve the heuristic function to accelerate the convergence speed; a random state transfer mechanism is adopted to improve the global search capability; secondly, we introduce an ant retreat strategy to ensure that each ant can escape from the trap, which solves the U-shaped of obstacle trap problem and improves the search efficiency. Finally, the effectiveness of the proposed algorithm is verified by experimental simulation.