Research on Path Planning of Mobile Robot Based on Improved Immune-Ant Colony Algorithm

In order to solve the problems of low search efficiency and easy to fall into local optimal solution when using traditional ant colony algorithm for path planning of mobile robots, an improved immune ant colony hybrid algorithm is proposed. Firstly, the optimal solution is obtained by using the fast global convergence of the immune algorithm, which is used as the initial pheromone distribution of the ant colony algorithm. On this basis, the improved ant colony algorithm is used for global path planning, which effectively solves the problem that the search efficiency is low due to the lack of pheromone in the early stage. By comparing the experimental results of the two algorithms, the advantages of hybrid algorithm are illustrated. The experimental results show that the improved Immune Ant Colony Algorithm can better solve the path planning problem of mobile robots in complex environments.