Conjugate Unscented Particle Filter Based Monte Carlo Localization for Mobile Robots

Jiang Xue Fei; Song Yu

doi:10.4028/www.scientific.net/AMM.556-562.2266

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Conjugate Unscented Particle Filter Based Monte...

Conjugate Unscented Particle Filter Based Monte Carlo Localization for Mobile Robots

Abstract:

For mobile robot localization in known environment, the 5^th-order Conjugate Unscented Particle Filter Monte Carlo Localization (CUPF-MCL) algorithm is proposed. CUPF-MCL combines the 5^th-order Conjugate Unscented Transform (5^th CUT) with Kalman Filter to generate more accuracy particle filter proposal distribution, calculating the transition density up to the 5^th-order nonlinearity. In simulation, the performance of CUPF-MCL is compared with that of dead reckoning, PF-MCL, EPF-MCL and UPF-MCL. Results show that CUPF-MCL improves the accuracy of localization.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

2266-2269

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.2266

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Online since:

May 2014

Authors:

Jiang Xue Fei*, Song Yu

Keywords:

Kalman Filter, Mobile Robot, Monte Carlo Localization (MCL), Particle Filter

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* - Corresponding Author

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