Adaptive Path Planning for Tracking Ocean Fronts with an Autonomous Underwater Vehicle

  • Ryan N. Smith
  • Philip Cooksey
  • Frederic Py
  • Gaurav S. Sukhatme
  • Kanna Rajan
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 109)

Abstract

Ocean fronts are productivity hot spots, supporting marine life from plankton to whales. These dynamic systems contain a vast amount of information, and have the potential to significantly expand our knowledge of aquatic ecosystems in relation to climate change. However, ocean fronts and other dynamic features cannot be studied through conventional oceanographic techniques. In this paper, we address the problem of sampling and tracking an ocean front with an Autonomous Underwater Vehicle based on predictions and/or priors provided by a heterogeneous team of assets and ocean models. Specifically, given a prior (that may not be accurate or up-to-date) we present a method for an underwater vehicle to plan a mission and adapt this mission on-the-fly to track a dynamic feature. Results from field trials are presented, and demonstrate that the vehicle is able to adapt its path to follow a desired contour.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ryan N. Smith
    • 1
  • Philip Cooksey
    • 2
  • Frederic Py
    • 3
  • Gaurav S. Sukhatme
    • 4
  • Kanna Rajan
    • 3
  1. 1.Physics and Engineering DepartmentFort Lewis CollegeDurangoUSA
  2. 2.California State University, Monterey BayMontereyUSA
  3. 3.Monterey Bay Aquarium Research InstituteMoss LandingUSA
  4. 4.Robotic Embedded Systems Laboratory and the Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA

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