Improving computational and memory requirements of simultaneous localization and map building algorithms
- 25 June 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 3, 2731-2736
- https://doi.org/10.1109/robot.2002.1013645
Abstract
Addresses the problem of implementing simultaneous localisation and map building (SLAM) in very large outdoor environments. A method is presented to reduce the computational requirement from /spl sim/O(N/sup 2/) to /spl sim/O(N), N being the states used to represent all the landmarks and vehicle pose. With this implementation the memory requirements are also reduced to /spl sim/O(N). This algorithm presents an efficient solution to the full update required by the compressed extended Kalman filter algorithm. Experimental results are also presented.Keywords
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