AB  - D-SLAM algorithm first described in [1] allows SLAM to be decoupled into solving a non-linear static estimation problem for mapping and a threedimensional 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. © Springer-Verlag Berlin/Heidelberg 2006.
AU  - Wang, Z
AU  - Huang, S
AU  - Dissanayake, G
DA  - 2006/09/27
DO  - 10.1007/11736592_14
EP  - 166
JO  - Springer Tracts in Advanced Robotics
PY  - 2006/09/27
SP  - 155
TI  - Implementation issues and experimental evaluation of D-SLAM
VL  - 25
Y1  - 2006/09/27
Y2  - 2026/05/21
ER  -