Simultaneous localization and sampled environment mapping based on a divide-and-conquer ideology

This paper presents an algorithm of simultaneous localization and sampled environment mapping (SLASEM) with a divide-and-conquer ideology to localize a robot and map large scale environments without using the environments' geometric parameters. The usage of sampled environment map (SEM) prevents the algorithm from being limited to structured environments which can be described by geometric parameters. The algorithm builds local maps in real-time firstly, then combines them by the means of divide and conquer. This enables the proposed algorithm to be an on-line algorithm. To combine two local maps, firstly the algorithm extracts corner points from the maps and uses them to update the maps. Then, the algorithm takes the signed orthogonal distance function as the virtual measurement function to update the local maps in detail. Finally, the two local maps are combined into one and the redundant environment samples are removed to make the map compact. The results of two real experiments validate the efficiency and the real-time capability of the proposed algorithm. Copyright © 2010 Acta Automatica Sinica. All rights reserved.