无线传感器环境下粒子群优化的多机器人协同定位研究

Cooperative multi-robot localization based on particle swarm optimization in the environment of wireless sensor

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。

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 robots＇ 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.