Over the last two decades, uncrewed aircraft have become more popular and much more advanced, completing missions that were previously unimaginable. With increases in quantity and quality of remotely piloted aircraft comes a need for improved Federal Aviation Administration (FAA) standards to ensure a safer airspace. The FAA has been working with development organizations including the RTCA (formerly the Radio Technical Commission for Aeronautics) and ASTM International (formerly the American Society for Testing and Materials) to draft rules for integrating these aircraft into the National Airspace System. This system encompasses the network of airports, air traffic control towers, facilities, information, rules, regulations, and procedures that govern aviation in the U.S. However, one inherent challenge for remotely piloted aircraft is the federal mandate that a pilot must “see and avoid” and “remain well-clear” of other aircraft to avoid collisions. The specifics of how uncrewed aircrafts, like drones, can see and be seen in the air consistently remains a challenge. In response, RTCA defined “well-clear” and outlined standards for a DAA airspace in “DO-365 – Minimum Operational Performance Standards (MOPS) for Detect and Avoid (DAA) Systems.” RTCA tapped the National Aeronautics and Space Administration (NASA) to test the new system and develop a working model of DAA software to show how uncrewed aircraft can safely steer clear of other planes and meet FAA safety standards. The NASA Langley Research Center developed Detect-and-AvoID Alerting Logic for Unmanned Systems (DAIDALUS) technology. DAIDALUS provides core algorithms for a DAA system, including detection, alerts, and maneuver guidance. DAIDALUS also has capabilities that account for measurement errors and improve sensor accuracy. DAIDALUS was first developed for participants in the development of the DO-365 standards guide. The users experimented to determine the timing of alerts, how guidance should be displayed, and much more. DO-365 included DAIDALUS as reference implementation of the detect and avoid logic and used it in the final safety analysis of the original version of the standard. The entire aviation community needs to follow the same standards, so the developers of DAIDALUS and NASA’s technology transfer office opted to release DAIDALUS under a NASA Open Source Agreement, hosted on Github.com, where it is easily accessible to the aviation industry and researchers. Organizations can immediately and directly use DAIDALUS and ask technical questions to the development team, who, in turn, use the feedback to improve the technology. DAIDALUS has significant advantages like the simple and flexible configuration of settings, reliable and consistent behavior, and open-source availability, which led to wide usage. The project aimed to identify technical barriers, which the team achieved through the first transfer of DAIALUS. The transfer allowed partner entities to research and experiment much faster than if they had to develop detect-and-avoid capabilities in-house. So far, Mosaic – or the FAA’s proposed “Modernization of Special Airworthiness Certification” rule that would put performance safety standards in place and expand the definition of a Light Sport Aircraft to increase safety, versatility, and accessibility – has integrated DAIDALUS. Mosaic and DAIDALUS mix with a system that uses Remote ID (a drone’s ability to broadcast in-flight identification and location information) to prevent collisions between drones. UPS and Raytheon have also integrated a version of DAIDALUS in their UPS Flight Forward system that uses drones to deliver packages. And the Naval Air Systems Command has integrated the technology into its ground-based detect-and-avoid system and approved its use within military space. NASA’s Langley Research Center developed DAIDALUS to keep up with the growth and advancement of uncrewed aircraft and ensure that they can cooperate in our airspace, ensuring better safety and high-quality on-board technology. This technology received a 2025 FLC Excellence in Technology Transfer Award. Learn more here and discover more awardees in our Awards Gallery.