Current-Sensitive Path Planning for an Underactuated Free-floating Ocean Sensorweb
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.
Additional Information
© 2011 IEEE. Date of Current Version: 05 December 2011. The research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology. Copyright 2011 California Institute of Technology. All Rights Reserved. US Government Support Acknowledged.Additional details
- Eprint ID
- 30022
- Resolver ID
- CaltechAUTHORS:20120406-142747616
- Created
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2012-04-06Created from EPrint's datestamp field
- Updated
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2021-11-09Created from EPrint's last_modified field
- Series Name
- IEEE International Conference on Intelligent Robots and Systems