DocumentCode :
2411516
Title :
Online model estimation of ultra-wideband TDOA measurements for mobile robot localization
Author :
Prorok, Amanda ; Gonon, Lukas ; Martinoli, Alcherio
Author_Institution :
Distrib. Intell. Syst. & Algorithms Lab., Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland
fYear :
2012
fDate :
14-18 May 2012
Firstpage :
807
Lastpage :
814
Abstract :
Ultra-wideband (UWB) localization is a recent technology that promises to outperform many indoor localization methods currently available. Yet, non-line-of-sight (NLOS) positioning scenarios can create large biases in the time-difference-of-arrival (TDOA) measurements, and must be addressed with accurate measurement models in order to avoid significant localization errors. In this work, we first develop an efficient, closed-form TDOA error model and analyze its estimation characteristics by calculating the Cramér-Rao lower bound (CRLB). We subsequently detail how an online Expectation Maximization (EM) algorithm is adopted to find an elegant formalism for the maximum likelihood estimate of the model parameters. We perform real experiments on a mobile robot equipped with an UWB emitter, and show that the online estimation algorithm leads to excellent localization performance due to its ability to adapt to the varying NLOS path conditions over time.
Keywords :
expectation-maximisation algorithm; indoor environment; measurement systems; mobile robots; path planning; position control; time-of-arrival estimation; ultra wideband technology; CRLB; Cramer-Rao lower bound; EM algorithm; NLOS path conditions; NLOS positioning scenarios; UWB emitter; UWB localization; closed-form TDOA error model; estimation characteristics; indoor localization methods; localization errors; maximum likelihood estimation; measurement models; mobile robot localization; model parameters; nonline-of-sight positioning scenarios; online estimation algorithm; online expectation maximization algorithm; online model estimation; time-difference-of-arrival measurements; ultra-wideband TDOA measurements; Base stations; Equations; Estimation; Mathematical model; Measurement uncertainty; Position measurement; Robots;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2012 IEEE International Conference on
Conference_Location :
Saint Paul, MN
ISSN :
1050-4729
Print_ISBN :
978-1-4673-1403-9
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ICRA.2012.6224869
Filename :
6224869
Link To Document :
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