基于改进蚁群算法的火源定位策略研究

为了达到多机器人系统能够模仿蚁群寻找食物源的行为来定位搜索火源目标,对基本蚁群算法和禁忌搜索算法进行融合和修正,形成一种新的目标搜索策略。修正的蚁群算法包括:全局随机搜索、局部遍历搜索和信息素更新三个部分。在搜索过程中,通过设定信息素的有效作用范围来实现对多个火源目标的定位。仿真结果表明,局部遍历搜索能够保证机器人逐步靠近火源目标,而融合了禁忌搜索的蚁群算法在搜索效率上大大提高。

Fire localization strategy based on modified Ant Colony Algorithm

For robots searching for the fire sources by foraging behavior of art colony,a multi-robots search strategy is proposed by combing and modifying Ant Colony Algorithm（ACA）and Tabu Search algorithm（TS）.The modified ACA includes three parts,which are global random search,local traversal search and pheromone update.In the search process,an effective range of pheromone is set to localize multiple fire sources.Simulation results show that the local traversal search can enable robots to move towards the fire gradually,and search efficiency is improved.