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Autonomous Undersea Vehicle Track Planner (AUVTP) for Adaptive Environmental Sampling

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00039-05-C-0055
Agency Tracking Number: N051-080-0766
Amount: $69,484.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N05-080
Solicitation Number: 2005.1
Timeline
Solicitation Year: 2005
Award Year: 2005
Award Start Date (Proposal Award Date): 2005-08-01
Award End Date (Contract End Date): 2006-04-12
Small Business Information
40 Lloyd Avenue, Suite 200
Malvern, PA 19355
United States
DUNS: 075485425
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 David Kierstead
 Vice President
 (703) 938-2032
 kierstea@nva.wagner.com
Business Contact
 John Eldridge
Title: Treasurer
Phone: (610) 644-3400
Email: GovtMktg@pa.wagner.com
Research Institution
N/A
Abstract

Environmental conditions can have a significant effect on Naval planning efforts and operations. To gain a warfare advantage, information obtained through in-situ observations and measurements of environmental properties (e.g., water depths, currents, temperature, salinity, wave spectra) can be exploited to improve the planning and execution of these operations. Such information is critical in littoral environments to support reliable wave and surf model predictions. Increasingly, mobile observational platforms, such as AUVs, are playing a greater role in the data collection process in littoral waters (due to their covertness, efficiency, increasing viability, and reduced risks). Daniel H. Wagner, Associates (DHWA), teamed with the Neptune Sciences Division of Planning Systems, Inc., proposes to develop an adaptive sampling track-planning system, for one or more AUVs, to maximize the value of data collected and achieve mission objectives. There are two major goals. The first is to investigate and develop methods to determine, prioritize, and quantify the data collection needs (spatially and temporally). The second is to develop a track-planning tool using a genetic algorithm approach, leveraging an existing algorithm developed by DHWA for ASW search planning. This tool will be the first step toward an expanded capability for other types of platforms and missions.

* Information listed above is at the time of submission. *

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