SBIR-STTR Award

Autonomous Decision Support System for Sense and Avoid (ADeSSSA)
Profile last edited on: 9/5/2022

Program
SBIR
Agency
NASA | LaRC
Total Award Amount
$874,559
Award Phase
2
Principal Investigator
James Peverill
Activity Indicator

Company Information

GreenSight Agronomics (AKA:GreenSight Inc)

12 Channel Street Suite 605
Boston, MA 02210
   (844) 484-7336
   info@greensightag.com
   www.greensightag.com
Multiple Locations:   
Congressional District:   08
County:   Suffolk

Phase I

Phase I year
2021
Phase I Amount
$124,559
GreenSight proposes ADeSSSA, the Autonomous Decision Support System for Sense and Avoid, a novel approach for unmanned aircraft sense and avoid, combining wide field of view visual sensors with acoustic sensing to improve the effectiveness of the resulting implementation while reducing its Size, Weight, Power and Cost implementation. GreenSight intends to use a mix of deep learning techniques to build an ideal classifier that ingests samples that combine the visual and acoustic sensors into a visual representation. ADS-B transponder data is incorporated as both a source of low-false positive data and as a filter to facilitate automated gathering of training data. ADeSSSA is designed to accommodate low SWaPC applications such as unmanned aircraft as small as 2kg, a niche that is currently unoccupied. There are no practical sense and avoid systems on the market for platforms this small, which is currently hurting the growth of the commercial UAS market, and slowing NASA and the FAA's efforts to build an integrated next generation airspace which integrates these smaller aircraft. GreenSight maintains a network of over 100 automated UAS which currently operate daily in the US, Canada, Europe and Japan. Once ADeSSSA is ready for field use, GreenSight can immediately deploy the system to its entire network, instantly becoming the most widely deployed UAS SAA system in the world and enabling it to rapidly mature with extensive field testing to find and correct weaknesses in the implementation. Potential NASA Applications (Limit 1500 characters, approximately 150 words): ADeSSSA addresses NASA requirements to enable low-SWaPC sense and avoid technology, as well as furthering efforts to modernize the national airspace and integrate unmanned aircraft with the current manned aircraft-centric system. ADeSSSA enables next generation Urban Air Mobility and Advanced Aerial Mobility systems, while also furthering the ability of commercial UAS in markets where fear of collisions is restricting flight operations that are otherwise safe. Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words): ADeSSSA has extensive applications in both military and commercial UAS. GreenSight envisions integrating the system with all of its existing UAV products, from the 2kg Dreamer to the 200kg EndureMax. Beyond this, GreenSight intends to commercialize and sell ADeSSA for unmanned aircraft of a variety of sizes operating in mixed airspace, becoming the global standard for onboard UAV sense and avoid. Duration: 6

Phase II

Phase II year
2022 (last award dollars: 2022)
Phase II Amount
$750,000
GreenSight’s ADeSSSA is a new sense and avoid system which enables autonomous decision making by UAVs of all sizes in order to actively sense, assess and avoid collisions. GreenSight’s approach uniquely fuses 360-degree visual sensing with acoustic and transponder sensing. While there have been research projects and some early commercial products which have explored this approach, none have created a verifiable framework which can be used to accurately guide autonomous systems. Point solutions, such as those using machine vision or ADS-B receivers, are in limited use but are not robust enough to support safety or mission-critical autonomous services. As a result, no currently available commercial systems provide effective sense and avoid for UAS. GreenSight’s ADeSSSA is a framework which combines multiple sensor modalities (visual, acoustic and transponder) into a probabilistic safety estimate. This information is used to feed autonomous decision systems on an aircraft and guide flight trajectory planning. ADeSSSA will be immediately relevant to small unmanned aircraft, and extensible in the future to more safety critical systems like self-piloting UAM aircraft. Potential NASA Applications (Limit 1500 characters, approximately 150 words): ADeSSSA has potential to positively impact multiple NASA programs directly and indirectly using UAS. NASA has extensive programs on UAS airspace integration and AAM. Some of the specific programs that are relevant and will be furthered by ADeSSSA include: Advanced Air Mobility (AAM High Density VertiPlex (HDV) System-Wide Safety (SWS) Scalable Traffic Management for Emergency Response Operations (STEReO) UAS Traffic Management (UTM) Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words): As operators of UAS that desire to utilize them in mixed airspace, the US DoD and other federal agencies will benefit directly from ADeSSSA. GreenSight completed a project earlier in 2021 using sUAS for airfield safety inspections at military bases. ADeSSSA would allow these systems to detect and react to air traffic in the event of an air traffic management mistake, averting a collision. Duration: 18