An Evaluation of Sampling Path Strategies for an Autonomous Underwater Vehicle Conference Paper

abstract

• A critical problem in planning sampling paths for autonomous underwater vehicles is balancing obtaining an accurate scalar field estimation against efficiently utilizing the stored energy capacity of the sampling vehicle. Adaptive sampling approaches can only provide solutions when real-time and a priori environmental data is available. Through utilizing a cost-evaluation function to experimentally evaluate various sampling path strategies for a wide range of scalar fields and sampling densities, it is found that a systematic spiral sampling path strategy is optimal for high-variance scalar fields for all sampling densities and low-variance scalar fields when sampling is sparse. The random spiral sampling path strategy is found to be optimal for low-variance scalar fields when sampling is dense. 2012 IEEE.

name of conference

• 2012 IEEE International Conference on Robotics and Automation

authors

• Saripalli, Srikanth

published proceedings

• 2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)

author list (cited authors)

• Ho, C., Mora, A., & Saripalli, S.

citation count

• 3

complete list of authors

• Ho, Colin||Mora, Andres||Saripalli, Srikanth

publication date

• May 2012

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Conference on Robotics and Automation  Journal

Digital Object Identifier (DOI)

• 10.1109/icra.2012.6225231

International Standard Book Number (ISBN) 13

• 9781467314039

start page

• 5328

end page

• 5333

volume

• 1

URL

• http://dx.doi.org/10.1109/icra.2012.6225231