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Proceedings Paper

The telesupervised adaptive ocean sensor fleet
Author(s): Alberto Elfes; Gregg W. Podnar; John M. Dolan; Stephen Stancliff; Ellie Lin; Jeffrey C. Hosler; Troy J. Ames; John Moisan; Tiffany A. Moisan; John Higinbotham; Eric A. Kulczycki
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Paper 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.

Paper Details

Date Published: 24 September 2007
PDF: 11 pages
Proc. SPIE 6684, Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS, 668411 (24 September 2007); doi: 10.1117/12.735561
Show Author Affiliations
Alberto Elfes, Jet Propulsion Lab. (United States)
Gregg W. Podnar, Carnegie Mellon Univ. (United States)
John M. Dolan, Carnegie Mellon Univ. (United States)
Stephen Stancliff, Carnegie Mellon Univ. (United States)
Ellie Lin, Carnegie Mellon Univ. (United States)
Jeffrey C. Hosler, NASA Goddard Space Flight Facility (United States)
Troy J. Ames, NASA Goddard Space Flight Facility (United States)
John Moisan, NASA Wallops Flight Facility (United States)
Tiffany A. Moisan, NASA Wallops Flight Facility (United States)
John Higinbotham, Emergent Space Technologies (United States)
Eric A. Kulczycki, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 6684:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS
Mitchell D. Goldberg; Hal J. Bloom; Allen H.-L. Huang; Philip E. Ardanuy, Editor(s)

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