STTR Phase I: Autonomous Landing of sUAS onto Moving Platforms

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 1648563
Agency Tracking Number: 1648563
Amount: $224,912.00
Phase: Phase I
Program: STTR
Awards Year: 2017
Solicitation Year: 2016
Solicitation Topic Code: EW
Solicitation Number: N/A
Small Business Information
710 13TH ST UNIT 307, SAN DIEGO, CA, 92101-7351
DUNS: 079592990
HUBZone Owned: Y
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Gaemus Collins
 (805) 453-3122
Business Contact
 Gaemus Collins
Phone: (805) 453-3122
Research Institution
 Brigham Young University
 Randal W Beard
 Multiple AGent Intelligent Coordination and Control Lab
459 Clyde Building
Provo, UT, 84602
 Nonprofit college or university
The broader impact/commercial potential of this project is the expansion of autonomous unmanned aerial systems (UAS, or drones) to new maritime operational environments and commercial markets. The proposed technology will enable small UAS to operate from vessels moving at sea, without the need for a dedicated pilot or installed hardware, even while far from shore and beyond the reach of established communication networks. Small UAS can offer the same aerial perspective provided by manned helicopters at a fraction of the size, cost, and risk. Real-time aerial imagery from UAS will supply maritime operators with invaluable information about their surroundings at sea, which is not available by any other means. This information is critical for many maritime applications, including fishing, ocean monitoring, scientific exploration, maritime surveillance, and search, and rescue. This information will offer a particularly large and immediate impact for 98% of worldwide commercial fishing vessels (those that do not carry embarked manned helicopters for fish-finding) by dramatically reducing their fuel costs; providing net economic and environmental gains for the industry. This Small Business Technology Transfer (STTR) Phase I project will develop algorithms and software to enable small UAS autonomously and reliably land onto a moving platform at sea. Commercially-available small UAS can offer invaluable real-time aerial imagery for maritime operators. But, this technology is not currently in widespread use due to technological barriers. In particular, the key enabling technology is the ability to autonomously and reliably land a small UAS onto a moving platform. The research objective is to develop algorithms and software that enable small UAS to autonomously operate from moving vessels at sea. Computer vision algorithms automatically detect the host vessel and the dedicated landing area. Data fusion algorithms estimate the relative drone-boat position and orientation in real time, including compensation for vessel roll, pitch, & heave. Precision control algorithms optimize the drone?s trajectory for save, reliable, autonomous launch and landing. A prototype system will be built by integrating the STTR-developed software with commercially available hardware components.

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

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