Monte Carlo localisation of a mobile robot using a Doppler-Azimuth radar

Guan, R, Ristic, B, Wang, L and Evans, R 2018, 'Monte Carlo localisation of a mobile robot using a Doppler-Azimuth radar', Automatica, vol. 97, pp. 161-166.

Document type: Journal Article
Collection: Journal Articles

Title Monte Carlo localisation of a mobile robot using a Doppler-Azimuth radar
Author(s) Guan, R
Ristic, B
Wang, L
Evans, R
Year 2018
Journal name Automatica
Volume number 97
Start page 161
End page 166
Total pages 6
Publisher Pergamom Press
Abstract This paper investigates the moving robot localisation problem using a Doppler-Azimuth radar array. The solution is formulated in the framework of nonlinear/non-Gaussian estimation using a particle filter and a random finite set (RFS) model of measurements. The proposed approach assumes the availability of a feature-based map, radar measurements and robot odometry data. The associations between the measurements and the features of the map (landmarks) are unknown. The RFS model is adopted to deal with false and missed detections and uses Murty's algorithm to reduce computation when solving the association problem. The proposed particle filter incorporates the Kullback-Leibler Distance (KLD)-Sampling to reduce computational time. Monte-Carlo simulation results demonstrate the efficacy of the proposed algorithm.
Subject Signal Processing
Autonomous Vehicles
Keyword(s) Doppler radar
Mobile robot navigation
Monte Carlo localisation
Particle filter
Random finite sets
DOI - identifier 10.1016/j.automatica.2018.08.012
Copyright notice © 2018 Published by Elsevier Ltd. All rights reserved.
ISSN 0005-1098
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
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