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Object Avoidance for Unmanned Surface Vehicles (USVs)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N65538-05-M-0031
Agency Tracking Number: N043-219-0255
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N04-219
Solicitation Number: 2004.3
Timeline
Solicitation Year: 2004
Award Year: 2004
Award Start Date (Proposal Award Date): 2004-10-25
Award End Date (Contract End Date): 2005-11-25
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
 W. Reynolds Monach
 Vice President
 (757) 727-7700
 reynolds@va.wagner.com
Business Contact
 W. Monach
Title: Vice President
Phone: (757) 727-7700
Email: reynolds@va.wagner.com
Research Institution
N/A
Abstract

Daniel H. Wagner Associates, Inc. will develop an Object Avoidance for Unmanned Surface Vehicles (OAUSV) system that processes all available data, dynamically generates a Tactical Picture, an optimal route, and an object avoidance plan, and provides this information to the Unmanned Surface Vehicle (USV) control system and its operators. A key capability provided by OAUSV will be the ability to fuse data obtained by off-board systems (e.g., other ship's/aircraft/UVs' organic systems, Route Surveys, MCM systems) with own-USV data in real-time. In addition, we will utilize the contact data fusion and environmental data fusion algorithms developed in our Commander's Estimate of the Situation Tactical Decision Aid (CESTDA) and Current, Wind, and Wave Data Fusion (CWWDF) projects for ONR to determine a recommended route for the USV that minimizes ship vulnerability. As shown in our Cooperative Organic Mine Defense (COMID) work, the ability to utilize non-own-USV data will significantly improves the ability of the USV to maneuver around potentially threatening objects and dramatically reduces the number of false alarms. The primary algorithmic techniques that will be utilized in OAUSV are non-Gaussian and multiple hypothesis data registration and fusion, non-Gaussian optimization, and Bayesian inferential reasoning.

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

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