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Drone Modular Smart Pallet (DroneMSP)

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC20C0495
Agency Tracking Number: 205977
Amount: $124,997.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A2
Solicitation Number: SBIR_20_P1
Timeline
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-08-27
Award End Date (Contract End Date): 2021-03-01
Small Business Information
888 Easy Street
Simi Valley, CA 93065-1812
United States
DUNS: 611466855
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Stephen Oonk
 (805) 582-0582
 soonk@americangnc.com
Business Contact
 Emily Melgarejo
Phone: (805) 582-0582
Email: emelgarejo@americangnc.com
Research Institution
N/A
Abstract

To support the advancement of NASArsquo;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.

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

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