EKF based distributed cooperative localization for a multirobot team

Chuxi Li, Jieying Lu, W. Su
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引用次数: 1

Abstract

This paper studies distributed cooperative localization problem for a multirobot team with one leader and two followers. Each robot in the team is equipped local sensors and can exchange data with its neighbors through wireless communication network. A distributed localization algorithm is developed by using extended Kalman filter (EKF) scheme. In every sampling period, each member in the team estimates its local state based on its local measurements and neighbor's state estimation information sent from its neighbors at current sampling time or last sampling time. A simulation result shows that the algorithm is feasible.
基于EKF的多机器人团队分布式协同定位
研究了一个领队两个随从的多机器人团队的分布式协同定位问题。团队中的每个机器人都配备了本地传感器,并可以通过无线通信网络与邻居交换数据。采用扩展卡尔曼滤波(EKF)方案,提出了一种分布式定位算法。在每个采样周期中,团队中的每个成员根据其本地测量值和邻居在当前采样时间或上次采样时间发送的状态估计信息估计其本地状态。仿真结果表明该算法是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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