Where do you sample? - An autonomous underwater vehicle story

Colin Ho, Srikanth Saripalli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We present an experimental evaluation of various sampling path strategies for an Autonomous Underwater Vehicle. Both systematic and stratified random sampling path strategies were evaluated based upon their estimation accuracy for isotropic and anisotropic scalar fields, as well as the relative energy consumption. We present results from several experimental trials that shows that the stratified random sampling strategy minimizes estimation error for denser sample distributions, and the systematic sampling strategy minimizes estimation error for sparser sample distributions. Finally, we experimentally show that the systematic spiral path sampling strategy is the most energy efficient.

Original languageEnglish (US)
Title of host publicationROSE 2011 - IEEE International Symposium on Robotic and Sensors Environments, Proceedings
Pages119-124
Number of pages6
DOIs
StatePublished - 2011
Event2011 9th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2011 - Montreal, QC, Canada
Duration: Sep 17 2011Sep 18 2011

Other

Other2011 9th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2011
CountryCanada
CityMontreal, QC
Period9/17/119/18/11

Keywords

  • AUV
  • kriging
  • Sampling

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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  • Cite this

    Ho, C., & Saripalli, S. (2011). Where do you sample? - An autonomous underwater vehicle story. In ROSE 2011 - IEEE International Symposium on Robotic and Sensors Environments, Proceedings (pp. 119-124). [6058512] https://doi.org/10.1109/ROSE.2011.6058512