基于群体智能的目标搜索及路径规划机制

Swarm Intelligence Based Target Searching and Path Planning Mechanism

摘要: 随着万物互联新型业务迅速发展，为智能化目标搜索及路径规划带来新的机遇。当前目标搜索及路径规划方法主要依赖于路径相对固定的静态全局地图，面向障碍物动态变化导致路径不固定的情形往往难以应对。本文引入群体智能思想，结合分布式计算、信息正反馈及启发式搜索等方法，从不依赖于全局地图及可支持路径动态变化角度，提出基于改进蚁群优化的目标搜索及路径规划机制，在目标搜索中持续优化路径选择以适应路径动态变化，实现高效目标搜索及路径规划。

Abstract: With the rapid development of novel services under Internet of Everything, it brings new opportunities for intelligent target searching and path planning. Currently, target searching and path planning mainly depend on static global map of relatively fixed paths; it is hard to deal with the situation that paths are not fixed due to the dynamic change of obstacles. This paper, introducing the idea of swarm intelligence, by integrating the methods of distributed computing, information positive feedback, and heuristic search, proposes the ant colony optimization based target searching and path planning mechanism from the perspective of supporting dynamic path changing without global map. Thus, the path selection is continuously optimized to adapt to the dynamic changing path information, so as to achieve efficient target searching and path planning.