An Improved Ant Colony Algorithm of Robot Path Planning for Obstacle Avoidance

• Main Authors: Hong-Jun Wang, Yong Fu, Zhuo-Qun Zhao, You-Jun Yue
• Format: Article
• Language: English
• Published: Hindawi Limited 2019-01-01
• Series: Journal of Robotics
• Online Access: http://dx.doi.org/10.1155/2019/6097591

The obstacle avoidance in path planning, a hot topic in mobile robot control, has been extensively investigated. The existing ant colony algorithms, however, remain as drawbacks including failing to cope with narrow aisles in working areas, large amount of calculation, etc. To address above technical issues, an improved ant colony algorithm is proposed for path planning. In this paper, a new weighted adjacency matrix is presented to determine the walking direction and the narrow aisles therefore are avoided by redesigning the walking rules. Also, the best ant and the worst ant are introduced for the adjustment of pheromone to facilitate the searching process. The proposed algorithm guarantees that robots are able to find a satisfying path in the presence of narrow aisles. The simulation results show the effectiveness of the proposed algorithm.