Mobile Robot Navigation Algorithm Based on Ant Colony Algorithm with A* Heuristic Method

Abstract

In the complex environment, the path planning of mobile robot should not only requires a short path, but also avoids problems such as excessive path turns and poor environmental adaptability. Therefore, an improved ACO is proposed in this paper to realize efficient search of path planning in complex maps of mobile robots. The improved ACO uses the evaluation function of A* algorithm as the initial pheromone concentration to accelerate the convergence rate of the algorithm. Secondly, turning points are taken as part of the pheromone concentration. Finally, the optimal route is smoothed to reduce the number of turning points and the length of the route. The simulation results show that the comprehensive performance of the improved algorithm on the complex map is greatly improved, and it has better global search ability and convergence, and the number of iterations, path length and turn times are better.