Multiscale adaptive sampling in environmental robotics

Author

Hombal, Vadiraj ; Sanderson, Arthur ; Blidberg, D. Richard

Author_Institution

Dept. of Civil & Environ. Eng., Vanderbilt Univ., Nashville, TN, USA

fYear

2010

fDate

5-7 Sept. 2010

Firstpage

80

Lastpage

87

Abstract

Observation of spatially distributed oceanographic phenomena using sensor-enabled AUVs involves a trade-off between coverage and resolution. In this paper the performance of adaptive variation sensitive sample distributions in such a sensing task is evaluated under mission constraints such as finite measurement time and finite vehicle speed and compared to uniform sampling. The relative performance of the four algorithms considered is characterized in terms of localization of features in the test functions.

Keywords

environmental factors; mobile robots; oceanographic techniques; remotely operated vehicles; sampling methods; underwater vehicles; environmental robotics; finite measurement time; finite vehicle speed; mission constraint; multiscale adaptive sampling; sensor enabled AUV; spatially distributed oceanographic phenomena; Robot sensing systems; Sea measurements; Spatial resolution; Strontium; Time measurement; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Multisensor Fusion and Integration for Intelligent Systems (MFI), 2010 IEEE Conference on

Conference_Location

Salt Lake City, UT

Print_ISBN

978-1-4244-5424-2

Type

conf

DOI

10.1109/MFI.2010.5604463

Filename

5604463