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EKF based distributed cooperative localization for a multirobot team

Chuxi Li, Jieying Lu, Weizhou Su

Year
2016
Citations
3

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.

Keywords

Extended Kalman filterKalman filterComputer scienceSampling (signal processing)RobotState (computer science)Distributed algorithmInformation exchangeSimultaneous localization and mappingWireless

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