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Visual Algorithms for Navigation and Guidance of UAVs with Autonomous Relational Decisions (VANGUARD)

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W911NF19C0019
Agency Tracking Number: D18C-006-0078
Amount: $229,908.40
Phase: Phase I
Program: STTR
Solicitation Topic Code: ST18C-006
Solicitation Number: 18.C
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-03-28
Award End Date (Contract End Date): 2020-01-27
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Michael O'Meara
 Senior Robotics Software Engineer
 (617) 491-3474
 momeara@cra.com
Business Contact
 Yvonne Fuller
Phone: (617) 491-3474
Email: yfuller@cra.com
Research Institution
 Boston University
 Mr. Todd Conley Mr. Todd Conley
 
Trustees of Boston University 881 Commonwealth Avenue
Boston, MA 02215
United States

 (617) 353-4365
 Nonprofit college or university
Abstract

Unmanned systems play a critical role in military operations across a wide range of missions. The DoD’s Unmanned Systems Integrated Roadmap identifies leader-follower tactics, swarming capabilities, sensor advancements, collision avoidance, and GPS-denied solutions as key technologies to support autonomy. Advances in these areas are needed to support coordinated multi-aircraft maneuvers and swarm tactics, and robust visual relative navigation algorithms are needed to enable the successful use of heterogeneous robotic swarms. We propose to develop a lightweight, affordable, all-passive optical system onboard UAVs to visually navigate and maneuver relative to other non-cooperative aircraft in real-time with Visual Algorithms for Navigation and Guidance of UAVs with Autonomous Relational Decisions (VANGUARD). VANGUARD enables tactics and capabilities that support new CONOPS such as airborne launch and recovery, enemy airspace penetration, and UAV swarming/formation flying in GPS denied environments without inter-aircraft communication links. VANGUARD uses a bio-inspired, neuromorphic, dynamic vision sensor with ultra-low response latency and optical flow capabilities, our advanced Object Detection Framework (ODF), and deep-learning driven aircraft pose estimation to rapidly identify and respond to subtle maneuvers by the aircraft being followed. Our GeMFIRE flight simulator provides a simulation test bed for closed-loop system performance evaluation.

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

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