基于修正蚁群算法的多机器人气味源定位策略研究

为了使多机器人系统能够模仿蚁群寻找食物源的行为方式来搜索室内环境中存在的气味源，通过对蚁群算法的修正，形成一种新的多机器人协作策略．修正的蚁群算法包括局部遍历搜索、全局随机/概率搜索和信息素更新三个阶段．为了实现多个气味源的定位，在迭代搜索中加入了气味源确认机制．仿真结果表明，局部遍历搜索能够保证机器人逐步靠近气味源，而在全局搜索中设置气味浓度检测阈值可以避免机器人“群聚”现象的形成．最后验证了从不同入口点分散进入搜索区域时，机器人对多个气味源的搜索定位效果．

Multi-Robot Odor Source Localization Strategy Based on a Modified Ant Colony Algorithm

To enable robots to search for the indoor odor sources by imitating the foraging behavior of ant colony,a multi- robot cooperation strategy is proposed based on a modified ant colony algorithm(ACA).The modified ACA includes three stages,which are local traversal search,global random/probability search and pheromone update.A verification procedure is introduced into the iteration process to localize multiple odor sources.Simulation results show that the local traversal search can enable the robots to move to...