Path planning algorithm based on hybrid A* and adaptive ant colony optimization

摘要

It is challenging to plan the optimal and smooth path using the traditional path planning algorithm. This paper proposes a hybrid path planning algorithm based on the A* algorithm with quadratic node search and an adaptive Ant Colony Algorithm (ACO). Through the quadratic node search operation of the nodes on the path, the proposed algorithm reduces the length of the path planning and the number of turns and improves the efficiency of path planning. The ACO based on pheromone adjustment overcomes the shortcomings of traditional ACO, such as long search time and slow convergence speed, by adjusting pheromone and improving transition probability. The experimental results show that the proposed hybrid path planning algorithm has a better global search ability and convergence speed and achieves better results in robot path planning.