Rao-Blackwellized Posterior Linearization Backward SLAM
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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14
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IEEE Transactions on Vehicular Technology, Volume 68, issue 5, pp. 4734-4747
Abstract
This paper proposes the posterior linearisation backward simultaneous localisation 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-Blackwellised 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 linearisation to obtain Gaussian approximations of the distribution of the landmarks. PLB-SLAM is assessed via numerical simulations and real experiments for indoor localisation and mapping of radio beacons using a smartphone, Bluetooth beacons, and Wi-Fi access points.Description
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García-Fernández, Á F, Hostettler, R & Särkkä, S 2019, 'Rao-Blackwellized Posterior Linearization Backward SLAM', IEEE Transactions on Vehicular Technology, vol. 68, no. 5, 8662708, pp. 4734-4747. https://doi.org/10.1109/TVT.2019.2903569