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A Gaussian Process Regression Approach to Cooperative Sampling by Underwater Gliders

  • Tailang Yan
  • Zhiliang WuEmail author
  • Wenwen Wang
  • Lei Meng
  • Zhongxia Xiang
Conference paper
Part of the Mechanisms and Machine Science book series (Mechan. Machine Science, volume 73)

Abstract

Cooperative sampling with multiple underwater gliders is becoming popular for oceanographic observations. Development of efficient cooperative approaches has attracted people’s attention because direct energy acquisition from the ocean by the underwater vehicles is still at an early stage of research and the energy carried on board is quite limited. In this paper, we use a Gaussian Process Regression (GPR) approach to cooperating a group of underwater gliders. Assuming the observations follow a multivariate Gaussian distribution, the underwater gliders are directed toward the most informative direction that is predicted using previous observations by all the gliders in the group. Estimation of a simulated tempereature field is presented using the GPR approach. Comparison with the conventional lawnmower approach shows that the GPR approach is superior in accuracy and efficiency.

Keywords

Gaussian Progress Regression Underwater Glider Cooperative Sampling 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Tailang Yan
    • 1
  • Zhiliang Wu
    • 1
    Email author
  • Wenwen Wang
    • 1
  • Lei Meng
    • 1
  • Zhongxia Xiang
    • 1
  1. 1.School of Mechanical EngineeringTianjin UniversityTianjinChina

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