Improved ant colony algorithm for path planning based on pheromone difference distribution strategy
Year: 2024
Type: article
Abstract: In view of the problems of blind search in the initial stage, slow convergence speed and easy to fall into local optimum when the traditional ant colony algorithm is used for mobile robot path planning, an improved ant colony algorithm is proposed. Firstly, according to the distance between each node and the line connecting the starting point and the target point, the initial pheromone is unevenly distributed to make it normally distributed, which reduces the blindness of the algorithm search in the initial stage and speeds up the search for the optimal solution; secondly, the volatility factor is improved, and the principle of double volatility factor is adopted to control the volatility of pheromone, which not only reduces the possibility of local optimum but also speeds up the convergence speed; the redundant path is further optimized to make the path better. Simulation results show that the improved ant colony algorithm in this paper converges faster and more stably than the traditional ant colony algorithm and other improved ant colony algorithms.
Authors: Ma Kangkang, Wang Lei, Li Dongdong, Cai Jincao, Su Xueman
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4403385230