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Current-sensitive path planning for an underactuated free-floating ocean sensorweb

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dc.contributor.author Dahl, Kristen P.
dc.contributor.author Thompson, David R.
dc.contributor.author McLaren, David
dc.contributor.author Chao, Yi
dc.contributor.author Chien, Steve
dc.date.accessioned 2013-10-11T20:28:05Z
dc.date.available 2013-10-11T20:28:05Z
dc.date.issued 2011-09-23
dc.identifier.citation IEEE International Conference on Intelligent Robots and Systems, Special Marine Symposium, San Francisco, September 23, 2011. en_US
dc.identifier.clearanceno 11-2623
dc.identifier.uri http://hdl.handle.net/2014/43867
dc.description.abstract This work investigates multiagent path planning in strong, dynamic currents using thousands of highly underactuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats’ motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2011. en_US
dc.subject oceanography en_US
dc.subject Argo Floats en_US
dc.subject path planning en_US
dc.subject mission planning en_US
dc.subject robotics en_US
dc.title Current-sensitive path planning for an underactuated free-floating ocean sensorweb en_US
dc.type Preprint en_US


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