A Feature Based Navigation System for an Autonomous Underwater Robot

  • John Folkesson
  • Jacques Leederkerken
  • Rob Williams
  • Andrew Patrikalakis
  • John Leonard
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 42)


We present a system for autonomous underwater navigation as implemented on a Nekton Ranger autonomous underwater vehicle, AUV. This is one of the first implementations of a practical application for simultaneous localization and mapping on an AUV. Besides being an application of real-time SLAM, the implemtation demonstrates a novel data fusion solution where data from 7 sources are fused at different time scales in 5 separate estimators. By modularizing the data fusion problem in this way each estimator can be tuned separately to provide output useful to the end goal of localizing the AUV, on an a priori map. The Ranger AUV is equipped with a BlueView blazed array sonar which is used to detect features in the underwater environment. Underwater testing results are presented. The features in these tests are deployed radar reflectors.


Extended Kalman Filter Underwater Environment Extend Information Filter Predict Filter Sonar Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • John Folkesson
    • 1
  • Jacques Leederkerken
    • 1
  • Rob Williams
    • 1
  • Andrew Patrikalakis
    • 1
  • John Leonard
    • 1
  1. 1.Massachusetts Institute of Technology 

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