军事协同巡检路线优化策略

An improved cooperative ant colony optimization algorithm is proposed to enhance the inspection efficiency of large-scale inspection system with multiple robots. Each robot has an ant colony to search its inspection path, and a sharing taboo list is designed to implement the information interaction among the different ant colonies. The cost competitive mechanism is used to determine an ant among different ant colonies to search the inspection node. According to the distribution of the inspection nodes, the cooperative ant colony optimization algorithm could be used to accomplish the region segmentation and the path optimization simultaneously. Thus the inspection region could be segmented reasonably. Experimental results show that the cooperative ant colony optimization algorithm could be used to segment the inspection task more evenly than the conventional method based on map segmentation, which enhances the utilization rate of inspection robots, and the total inspection workload could be reduced. Therefore, the inspection performance could be improved significantly.