Affiliations:
Chongqing College of Electronic Engineering, Shapingba District, Chongqing, China
Correspondence:
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Corresponding author. Jinquan Liao, Chongqing College of Electronic Engineering, Shapingba District, Chongqing, China. Email: [email protected].
Abstract: With the rapid development of modern science and technology, more and more high-tech has appeared in front of the common people, in particular, the recent rise of artificial intelligent robots and other supernova scientific developments. In order to move the robot according to the direction of the system design, it is necessary to plan the robot’s walking path to a certain extent; this requires the use of specific algorithms to achieve. This paper was based on the application of path planning at the present stage, the artificial immune and ant colony fusion algorithm were used to plan and analyze the AGV path, the ant colony algorithm based on the artificial immune algorithm to enhance the recognition function of the immune system and the ant searching for food secretion pheromone as the optimal path finding method was the basic algorithm developed in this paper, the path planning of AGV was analyzed and studied.
Keywords: Immune algorithm, path planning, ant colony algorithm
