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Proceedings of the 18th IFAC World Congress

DOI: 10.3182/20110828-6-it-1002.02042

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A Nonlinear Least-Squares Approach to the SLAM Problem

Journal article published in 2011 by Zoran Sjanic, Martin A. Skoglund, Thomas B. Schön ORCID, Fredrik Gustafsson
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

In this paper we present a solution to the simultaneous localisation and mapping (SLAM) problem using a camera and inertial sensors. Our approach is based on the maximum a posteriori (MAP) estimate of the complete SLAM problem. The resulting problem is posed in a nonlinear least-squares framework which we solve with the Gauss-Newton method. The proposed algorithm is evaluated on experimental data using a sensor platform mounted on an industrial robot. In this way, accurate ground truth is available, and the results are encouraging.