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Published May 2010 | Published
Book Section - Chapter Open

Informative path planning for an autonomous underwater vehicle

Abstract

We present a path planning method for autonomous underwater vehicles in order to maximize mutual information. We adapt a method previously used for surface vehicles, and extend it to deal with the unique characteristics of underwater vehicles. We show how to generate near-optimal paths while ensuring that the vehicle stays out of high-traffic areas during predesignated time intervals. In our objective function we explicitly account for the fact that underwater vehicles typically take measurements while moving, and that they do not have the ability to communicate until they resurface. We present field results from ocean trials on planning paths for a specific AUV, an underwater glider.

Additional Information

© 2010 IEEE. This work was supported in part by the NOAA MERHAB program under grant NA05NOS4781228 and by NSF as part of the Center for Embedded Network Sensing (CENS) under grant CCR-0120778, by NSF grants CNS-0520305 and CNS-0540420, by the ONR MURI program (grants N00014-09-1-1031 and N00014-08-1-0693) by the ONR SoA program and a gift from the Okawa Foundation. Jonathan Binney was supported by a doctoral fellowship from USC. This research was partially supported by ONR grant N00014-09-1-1044 and a gift from Microsoft Corporation.

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September 25, 2023
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