NASA SBIR 2020-I Solicitation

Proposal Summary


PROPOSAL NUMBER:
 20-1- A2.02-5977
SUBTOPIC TITLE:
 Unmanned Aircraft Systems (UAS) Technologies
PROPOSAL TITLE:
 Drone Modular Smart Pallet (DroneMSP)
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
American GNC Corporation
888 Easy Street
Simi Valley, CA 93065
(805) 582-0582

Principal Investigator (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
Stephen Oonk
E-mail:
soonk@americangnc.com
Address:
888 Easy Street Simi Valley, CA 93065 - 1812
Phone:
(805) 582-0582

Business Official (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
Emily Melgarejo
E-mail:
emelgarejo@americangnc.com
Address:
888 Easy Street Simi Valley, CA 93065 - 1812
Phone:
(805) 582-0582
Estimated Technology Readiness Level (TRL) :
Begin: 3
End: 4
Technical Abstract (Limit 2000 characters, approximately 200 words)

To support the advancement of NASA’s Unmanned Aircraft Systems (UAS) technologies, specifically in the areas of: (a) verification, validation, and certification and (b) sensing, perception, cognition, decision making, American GNC Corporation (AGNC) and California State University, Northridge (CSUN) are proposing a new technology referred to as a Drone Modular Smart Pallet (DroneMSP). This smart pallet consists of a reconfigurable sensor suite, flexible interfacing unit, processing with SD-card memory, and power management. The components are housed in a small form-factor and lightweight frame that can be easily attached to and detached from different vehicles. This smart pallet is designed to be plug-and-play for use on low-cost, common commercial drones, instantly granting them with the smart capabilities of multi-modality sensing with data acquisition and online sensor fusion processing. This technology will instantly enable NASA scientists and many other researchers to test and deploy their own algorithms and sensors on commercial drones. The collected data can be input into in-flight processing algorithms but will also be saved in public repositories to facilitate research by diverse groups with the ultimate goal of advancing Urban Air Mobility (UAM) and the testing of technologies as needed for unmanned flight in the National Airspace. For demonstrating the utility of the smart pallet, an object recognition and collision avoidance Use Case is included which shows how the sensor suite can provide data to an algorithm to conduct a task of relevance to UAM. Key innovations include: (1) plug-and-play hardware and software; (2) flight optimized design; (3) embedded cognition with obstacle avoidance and (4) data labeling scheme for sensor quality generation.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

The DroneMSP system will advance the state-of-the-art of NASA’s unmanned aircraft systems by facilitating the deployment and testing of sensor payloads with data-fusion and intelligent algorithms. The smart pallet can be adapted for use on quadcopter drones, newer mid-sized designs such as the Langley Aerodome 8, and larger fixed wing unmanned aircraft for airborne remote science measurements. DroneMSP will benefit NASA research in safe and efficient Urban Air Mobility, for which centers such as AFRC, ARC, GRC, and LaRC are actively advancing.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

 

The DroneMSP will improve the ability of universities, laboratories, companies, students, and even hobbyists to conduct UAS research in a practical way. Commercial applications include inspection, agriculture, airborne sensing, surveying, delivery, construction and mining, imaging, etc. Government applications include traffic monitoring, search & rescue, border security, disaster management, etc.

Duration: 6

Form Generated on 06/29/2020 20:58:27