CAJ | 학술논문

考虑机器人间的通信受限约束,将机器人抽象为微粒,提出基于微粒群优化的多机器人气味寻源方法.首先,采用结合斥力函数的策略,引导机器人快速搜索烟羽;然后,基于无线信号对数距离损耗模型,估计机器人间的通讯范围,据此形成微粒群的动态拓扑结构,并确定微粒的全局极值;最后,将传感器的采样/恢复时间融入微粒更新公式,以跟踪烟羽.将所提出方法应用于3个不同场景的气味寻源,实验结果验证了该方法的有效性.
고필궤기인간적통신수한약속,장궤기인추상위미립,제출기우미립군우화적다궤기인기미심원방법.수선,채용결합척력함수적책략,인도궤기인쾌속수색연우;연후,기우무선신호대수거리손모모형,고계궤기인간적통신범위,거차형성미립군적동태탁복결구,병학정미립적전국겁치;최후,장전감기적채양/회복시간융입미립경신공식,이근종연우.장소제출방법응용우3개불동장경적기미심원,실험결과험증료해방법적유효성.
Considering the constraint of limited communication among robots, a method of localizing odor sources using multiple robots based on particle swarm optimization is presented on the condition of abstracting each robot as a particle. Firstly, a strategy incorporating with a repulsive function is utilized to guide a robot to rapidly search for a plume. Then the range of communication among robots is estimated based on the log-distance loss model of wireless signal propagation to form a dynamic topology structure of a particle swarm and to determine the global optimum of particles. Finally, the sampling/recovery time of a sensor is incorporated to update a particle so as to trace the plume. The proposed method is applied to localize odor sources in three various scenarios and the experimental results show its effectiveness.