Research on robot optimal path planning method based on improved ant colony algorithm

摘要

To overcome the problem of poor convergence and obstacle avoidance when traditional methods are used to plan the optimal path of robot, a new optimal path planning method based on improved ant colony algorithm is proposed. Firstly, the odometer model, ultrasonic sensor model and robot motion model are constructed to obtain the environmental information and robot motion state information. Then, according to the adaptive transformation heuristic function of the target point and the principle of wolf swarm assignment, the pheromone is refreshed. On this basis, the core parameters of the improved ant colony algorithm are optimised by particle swarm algorithm, so as to complete the optimal path planning of the robot. The experimental results show that the overall mean value of collision avoidance of the proposed method is 0.97, and the planning performance is significantly better than that of similar planning methods, with considerable application value.