Selective submap joining for underwater large scale 6-DOF SLAM

Josep Aulinas, Xavier Lladó, Joaquim Salvi, Yvan R. Petillot

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Autonomous Underwater Vehicles (AUVs) need positioning systems different than the Global Positioning System (GPS), which does not work in underwater scenarios. A possible solution to this lack of GPS signal are the Simultaneous Localization and Mapping (SLAM) algorithms. SLAM algorithms aim to build a map while simultaneously localize the vehicle within it. These algorithms suffer from several limitations in front of large scale scenarios. For instance, they do not perform consistent maps for large areas, mainly because uncertainties increase with the scenario. In addition, the computational cost increases with the map size. It has been demonstrated that the use of local maps reduces computational cost and improves map consistency. Following this idea, in this paper we propose a new SLAM technique based on using independent local maps, combined with a global level stochastic map. The global level contains the relative transformations between local maps. These local maps are updated once a new loop is detected and the amount of overlapping between local maps is high. Thus, maps sharing a high number of features are updated through fusion, maintaining the correlation between landmarks and vehicle. Experimental results on real data obtained from the REMUS-100 AUV show that our approach is able to obtain large map areas consistently. ©2010 IEEE.

Original languageEnglish
Title of host publicationIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings
Pages2552-2557
Number of pages6
DOIs
Publication statusPublished - 2010
Event23rd IEEE/RSJ International Conference on Intelligent Robots and Systems 2010 - Taipei, Taiwan, Province of China
Duration: 18 Oct 201022 Oct 2010

Conference

Conference23rd IEEE/RSJ International Conference on Intelligent Robots and Systems 2010
Abbreviated titleIROS 2010
CountryTaiwan, Province of China
CityTaipei
Period18/10/1022/10/10

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  • Cite this

    Aulinas, J., Lladó, X., Salvi, J., & Petillot, Y. R. (2010). Selective submap joining for underwater large scale 6-DOF SLAM. In IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings (pp. 2552-2557) https://doi.org/10.1109/IROS.2010.5650438