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FADS: A framework for autonomous drone safety using temporal logic-based trajectory planning

In this work, we present an integrated Framework for Autonomous Drone Safety (FADS). As surface congestion increases and the technology surrounding unmanned aerial systems (UAS) matures, more people are looking to the urban airspace and Urban Air Mobility (UAM) as a piece of the puzzle to promote mobility in cities. However, the lack of coordination between UAS stakeholders, federal UAS safety regulations, and researchers developing UAS algorithms continues to be a critical barrier to widespread UAS adoption. FADS takes into account federal UAS safety requirements, UAM challenge scenarios, contingency events, as well as stakeholder-specific operational requirements. Read more.

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Yash Vardhan Pant, Max Z. Li, Rhudii A. Quaye, Alena Rodionova, Houssam Abbas, Megan S. Ryerson, Rahul Mangharam (2021). FADS: A framework for autonomous drone safety using temporal logic-based trajectory planning.

Published in Transportation Research Part C: Emerging Technologies.

DOI: 10.1016/j.trc.2021.103275