Stereo Graph-SLAM for Autonomous Underwater Vehicles

  • Pep Lluis Negre CarrascoEmail author
  • Francisco Bonin-Font
  • Gabriel Oliver Codina
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)


The increasing use of Autonomous Underwater Vehicles (AUV) in industrial or scientific applications makes the vehicle localization one of the challenging questions to consider for the mission success. Graph-SLAM has emerged as a promising approach in land vehicles; however, due to the complexity of the aquatic media, these systems have been rarely applied in underwater vehicles. The few existing approaches are focused on very particular applications and require important amounts of computational resources, since they optimize the coordinates of the external landmarks and the vehicle trajectory, all together. This paper presents a simplified and fast general approach for stereo graph-SLAM, which optimizes the vehicle trajectory, treating the features out of the graph. Experiments with robots in aquatic environments show how the localization approach is effective underwater, online at 10 fps, and with very limited errors. The implementation has been uploaded to a public repository, being available for the whole scientific community.


Visual navigation Underwater robots Graph optimization 



This work is partially supported by the Spanish Ministry of Economy and Competitiveness under contracts PTA2011-05077 and DPI2011-27977-C03-02, FEDER Funding and by Govern Balear (Ref 71/2011). The authors are grateful to the members of the CIRS (University of Girona) for making available their facilities, including the AUV Girona500, used for some experiments.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Pep Lluis Negre Carrasco
    • 1
    Email author
  • Francisco Bonin-Font
    • 1
  • Gabriel Oliver Codina
    • 1
  1. 1.Systems, Robotics and Vision GroupUniversity of the Balearic Islands (UIB)Palma de MallorcaSpain

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