Implementation issues and experimental evaluation of D-SLAM

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2006, 25 pp. 155 - 166
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© Springer-Verlag Berlin Heidelberg 2006. D-SLAM algorithm first described in [1.] allows SLAM to be decoupled into solving a non-linear static estimation problem for mapping and a three-dimensional estimation problem for localization. This paper presents a new version of the D-SLAM algorithm that uses an absolute map instead of a relative map as presented in [1.]. One of the significant advantages of D-SLAM algorithm is its O (N) computational cost where N is the total number of features (landmarks). The theoretical foundations of D-SLAM together with implementation issues including data association, state recovery, and computational complexity are addressed in detail. Evaluation of the D-SLAM algorithm is provided using both real experimental data and simulations.
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