Rao-Blackwellized Posterior Linearization Backward SLAM

Garcia-Fernandez, Angel F ORCID: 0000-0002-6471-8455, Hostettler, Roland and Sarkka, Simo (2019) Rao-Blackwellized Posterior Linearization Backward SLAM. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 68 (5). pp. 4734-4747.

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Abstract

This paper proposes the posterior linearization backward simultaneous localization and mapping (PLB-SLAM) algorithm for batch SLAM problems. Based on motion and landmark measurements, we aim to estimate the trajectory of the mobile agent and the landmark positions using an approximate Rao-Blackwellized Monte Carlo solution, as in FastSLAM. PLB-SLAM improves the accuracy of current FastSLAM solutions due to two key aspects: smoothing of the trajectory distribution via backward trajectory simulation and the use of iterated posterior linearization to obtain Gaussian approximations of the distribution of the landmarks. PLB-SLAM is assessed via numerical simulations and real experiments for indoor localization and mapping of radio beacons using a smartphone, Bluetooth beacons, and Wi-Fi access points.

Item Type:	Article
Uncontrolled Keywords:	Simultaneous localization and mapping, backward simulation, posterior linearization, Rao-Blackwellization, Bluetooth beacons, Wi-Fi access points, smartphone
Depositing User:	Symplectic Admin
Date Deposited:	11 Mar 2019 08:26
Last Modified:	17 Mar 2024 03:12
DOI:	10.1109/TVT.2019.2903569
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3034026