CAJ | 학술논문

协同定位是多机器人自主行为的一项重要技术，重点描述了无线传感器网络环境下结合粒子群优化提出多机器人协同定位算法。该算法引入重采样，解决了粒子耗尽问题，扩大了解空间的范围，保证了种群的多样性，并且引入了惯性权重解决了粒子退化的问题。仿真结果表明，利用无线传感器网络进行辅助导航，采用粒子群优化算法，综合无线传感器网络进行辅助导航，融合各个机器人观测信息，可以降低求解问题的空间维数，在高斯噪声下能有效提高移动机器人定位精度。
협동정위시다궤기인자주행위적일항중요기술，중점묘술료무선전감기망락배경하결합입자군우화제출다궤기인협동정위산법。해산법인입중채양，해결료입자모진문제，확대료해공간적범위，보증료충군적다양성，병차인입료관성권중해결료입자퇴화적문제。방진결과표명，이용무선전감기망락진행보조도항，채용입자군우화산법，종합무선전감기망락진행보조도항，융합각개궤기인관측신식，가이강저구해문제적공간유수，재고사조성하능유효제고이동궤기인정위정도。
Cooperative localization is an important technique of multi-robot ’ s autonomous behavior .In this paper , the multi-robot cooperative localization algorithm based on the optimization of particle swarm optimization under wireless sensor network environment is described .The resampling algorithm is introduced to solve the problem of particle depletion , enlarge the scope of solution space and guarantee the diversity of population .The introduction of inertia weight provides a solution for the particle degradation .Simulation results showed that by using the particle swarm optimization algorithm , which is supported by wireless sensor network to assist navigation and integrating ro-bots’ observation information , the spatial dimensions of the problem can be reduced .In addition, the accuracy of robot localization can be improved effectively under the background of Gaussian noise .