Path Planning of Multiple Industrial Mobile Robots Based on Ant Colony Algorithm

At present, there are many problems in the research of multi-robot path planning, such as low efficiency of path planning algorithm, easy to fall into local optimum, and insufficient consideration of the application environment of robots. In order to improve the efficiency of multi-robot path planning algorithm, this paper generates dynamic change information according to the difference between the best path of the previous generation and the best path of the current iteration in ant colony algorithm, and improves the efficiency of the algorithm by the positive feed-forward generated by the dynamic change information, and adds mutation operation to the improved ant colony algorithm to solve the problem that the algorithm is easy to fall into local optimum. At the same time, on the premise of fully considering the working state of the robot and the urgency of the task, the rules of obstacle avoidance are optimized to improve the efficiency of obstacle avoidance of the robot and make the path planning of the multi-robot meet the requirements of the dynamic environment of the production workshop. The simulation results show the effectiveness of the algorithm.