Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

Joaquim Salvi, Yvan Petillot, Elisabet Batlle

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

17 Citations (Scopus)

Abstract

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed. ©2008 IEEE.

Original languageEnglish
Title of host publication2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Pages1011-1016
Number of pages6
DOIs
Publication statusPublished - 2008
Event21st IEEE/RSJ International Conference on Intelligent Robots and Systems 2008 - Nice, France
Duration: 22 Sep 200826 Sep 2008

Conference

Conference21st IEEE/RSJ International Conference on Intelligent Robots and Systems 2008
Abbreviated titleIROS 2008
CountryFrance
CityNice
Period22/09/0826/09/08

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  • Cite this

    Salvi, J., Petillot, Y., & Batlle, E. (2008). Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles. In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS (pp. 1011-1016) https://doi.org/10.1109/IROS.2008.4650627