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Design and simulation of a novel indoor mobile robot localization method using a light-emitting diode positioning system

Ngoc-Tan Nguyen, Anan Suebsomran, Keattisak Sripimanwat, Nam-Hoang Nguyen

Year
2015
Citations
12

Abstract

A key problem of mobile robots is that of the positioning capability in order to detect their locations in the operating environment. A promising technology used in indoor localization recently is Visible Light Communication (VLC). In this paper, an integrated Angle of Arrival-Received Signal Strength (AOA-RSS) localization method using the VLC, which could get high accuracy with simple hardware, is proposed. In addition, the Extended Kalman Filter (EKF) and Particle Filter (PF) algorithms are combined with the proposed AOA-RSS localization method in order to achieve higher accuracy of the mobile robot positioning. By computer simulation, the performance of the proposed AOA-RSS localization method combined with the EKF and PF algorithms are compared. The combination scheme outperforms the individual VLC localization with small error approximation of a few centimetres.

Keywords

RSSExtended Kalman filterVisible light communicationMobile robotComputer scienceParticle filterRobotReal-time computingKey (lock)Wireless

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