Xu, Jeffrey (University of Kansas), Keshmiri, Shawn (University of Kansas)

Dubins-Based Autolanding Procedure for Fixed-Wing UAS

Scheduled for presentation during the Regular Session "Path Planning I" (WeA3), Wednesday, June 16, 2021, 11:50−12:10, Edessa

2021 International Conference on Unmanned Aircraft Systems (ICUAS), June 15-18, 2021, Athens, Greece

This information is tentative and subject to change. Compiled on May 1, 2024

Abstract

Unmanned aerial systems are quickly growing in usage in both military and civilian applications. Unmanned aerial systems are quickly growing in usage in both military and civilian applications. The exponential growth in applications of unmanned aerial systems has provided many new opportunities such as urban air mobility. With the imminent entrance of unmanned aerial systems to the national airspace aircraft will be flying at lower heights over people and properties and will be landing in spatially constraint landing fields. Piloting UASs is an extremely exhausting endeavor, especially when complexities like landing in constraint spaces is involved. This paper introduces cognitive autolanding algorithms, where the standard landing stages of flare, glideslope, and approach, are employed to land the aircraft safely and the same time spatial and aircraft dynamic constraints are satisfied efficiently. The use of Dubins paths during the approach stage is explored and employed in this work showing how algorithms can be used to direct the aircraft towards any landing field from adverse initial headings and positions. The autolanding generated path is then flown in a six-degrees-of-freedom simulation environment. The robustness of this cognitive autolanding algorithm is validated using Monte Carlo analysis.