A Path Planning Method of Logistics Robot Based on Improved Ant Colony Algorithm
Ran Xu, Qi Zhang, Fen Ge
Abstract
One of the key technologies of logistics robot indoor navigation is path planning. Traditional ant colony algorithm is often used in the path planning of logistics robot, which has the problems of slow convergence and local optimization. We proposed an improved algorithm, that was used in path planning for logistics robots. Introducing a heuristic factor in the path transition probability can dynamically adjust the state transition probability, so that the algorithm avoids stagnation and improves the strategy of pheromone update. The paper carried out simulation experiments on the improved algorithm through the matlab software platform. From the simulation results, we can see that the path length of the improved algorithm is shorter, and the number of iterations is reduced by 23%.