The Telesupervised Adaptive Ocean Sensor Fleet

Alberto Elfes, Gregg Podnar, John M. Dolan, Stephen B. Stancliff, Ellie Lin Ratliff, Jeff Hosler, T. Ames, John Moisan, Tiffany Moisan, J. Higinbotham, and E. Kulczycki
Proceedings of the SPIE Conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS, August, 2007.


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Abstract
We are developing a multi-robot science exploration architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF uses a group of robotic boats (the OASIS platforms) to enable in-situ study of ocean surface and sub-surface phenomena. The OASIS boats are extended-deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. It allows multiple mobile sensing assets to function in a cooperative fashion, and the operating mode of the vessels to range from autonomous control to teleoperated control. In this manner, TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for tasking, control, and monitoring. It combines and extends prior related work done by the authors and their institutions. The TAOSF architecture is applicable to other areas where multiple sensing assets are needed, including ecological forecasting, water management, carbon management, disaster management, coastal management, homeland security, and planetary exploration. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). Several components of the TAOSF system have been tested, including the OASIS boats, the communications and control interfaces between the various hardware and software subsystems, and an airborne sensor validation system. Field tests in support of future HAB characterization were performed under controlled conditions, using rhodamine dye as a HAB simulant that was dispersed in a pond. In this paper, we describe the overall TAOSF architecture and its components, discuss the initial tests conducted and outline the next steps.

Notes
Associated Lab(s) / Group(s): Tele-Supervised Autonomous Robotics
Associated Project(s): Telesupervised Adaptive Ocean Sensor Fleet
Number of pages: 11

Text Reference
Alberto Elfes, Gregg Podnar, John M. Dolan, Stephen B. Stancliff, Ellie Lin Ratliff, Jeff Hosler, T. Ames, John Moisan, Tiffany Moisan, J. Higinbotham, and E. Kulczycki, "The Telesupervised Adaptive Ocean Sensor Fleet," Proceedings of the SPIE Conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS, August, 2007.

BibTeX Reference
@inproceedings{Elfes_2007_5843,
   author = "Alberto Elfes and Gregg Podnar and John M Dolan and Stephen B Stancliff and Ellie Lin Ratliff and Jeff Hosler and T. Ames and John Moisan and Tiffany Moisan and J. Higinbotham and E. Kulczycki",
   title = "The Telesupervised Adaptive Ocean Sensor Fleet",
   booktitle = "Proceedings of the SPIE Conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS",
   month = "August",
   year = "2007",
}