湍流烟羽环境下多机器人主动嗅觉实现方法研究

给出了一种用于实现主动嗅觉(也称气味/气体源定位或化学烟羽跟踪)的多机器人协同搜索策略. 将蚁群算法与逆风搜索相结合用于协调多机器人的运动方向. 蚁群算法可有效调动机器人朝信息素高的区域运动且保证机器人之间的距离不会过大; 逆风搜索可降低算法过早地陷入局部最优的概率. 为正确判断转移方向, 蚁群算法中还增加了对历史信息的考虑. 在源头确认方面, 本文提出了气味/气体浓度持久性判断结合机器人旋转计算流体质量通量散度的方法. 仿真表明, 本文的主动嗅觉搜索策略可适用于湍流烟羽环境, 且可有效地逃脱浓度局部最优和风场的漩涡, 另外可最终确认源头位置.

Study on Realization Method of Multi-robot Active Olfaction in Turbulent Plume Environments

This paper presents a cooperative search strategy based on multiple mobile robots to realize the active olfaction (also called odour/gas source localization or chemical plume tracing).Ant colony algorithm (ACA) combined with upwind search is used to coordinate swarm robots' motion.The ACA can effectively make most robots move toward the high-pheromone area and guarantee the distances among robots not too far.The upwind search can decrease the probability of robots trapping in local optimization too early.To judge the correct motion direction,the history pheromone is also considered in the ACA.The method of combining high-concentration maintenance criterion and fluid mass flux divergence calculation is put forward to recognize the odour/gas source.Computer simulations show that the proposed search strategy can work in turbulent environments.Using this strategy,the robots can escape from both local high concentration and eddy areas.In addition,the odour/gas source can be correctly declared finally.