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Communication Planning for Cooperative Terrain-Based Underwater Localization.

Jacob Anderson1, Geoffrey A Hollinger1

  • 1Collaborative Robotics and Intelligent Systems Institute, Oregon State University, Corvallis, OR 97331, USA.

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|April 3, 2021
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Summary
This summary is machine-generated.

This study introduces a decentralized algorithm for autonomous underwater vehicles to plan communications, significantly reducing bandwidth use and enhancing navigation accuracy through efficient scheduling.

Keywords:
acoustic communicationautonomous underwater vehiclesterrain-based navigation

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Area of Science:

  • Robotics
  • Navigation Systems
  • Communication Networks

Background:

  • Cooperative terrain-based navigation (dec-TBN) is crucial for autonomous underwater vehicles (AUVs).
  • Efficient communication planning is vital for optimizing dec-TBN performance and resource usage.

Purpose of the Study:

  • To develop and validate a decentralized communication planning algorithm for dec-TBN in AUVs.
  • To assess the algorithm's impact on communication bandwidth and localization accuracy.

Main Methods:

  • Utilized forward simulation to estimate communication value at each time step.
  • Constructed a directed acyclic graph for minimum cost communication scheduling.
  • Validated the algorithm through simulations using real-world bathymetry data and field trials with AUVs.

Main Results:

  • Simulations showed an 86% reduction in communication bandwidth and up to 27% improvement in localization accuracy.
  • Field trials demonstrated a 56% reduction in acoustic communication bandwidth in three out of four missions, with maintained localization.
  • The algorithm achieved 86% of localization accuracy using only 9% of communication bandwidth in one mission.

Conclusions:

  • The proposed communication planning algorithm effectively maintains or enhances dec-TBN accuracy.
  • The algorithm significantly reduces communication overhead, making cooperative navigation more efficient for AUVs.