Navigation and coordination of fixed-wing unmanned aerial vehicles under mission uncertainty

Unmanned Aerial Vehicles (UAVs) have been emerging as a promising but challenging platform for studying autonomous and cooperative control. This Ph.D. thesis focuses on fixed-wing UAVs which, with their more efficient aerodynamics, can ensure longer flight durations and more autonomy than multi-rotorUAVs. However, in the current state of the art, limited work has been done on deploying formations of fixed-wing UAVs that can operate autonomously even in the presence of large uncertainties. Uncertainties in fixed-wing UAVs include uncertain wind environments, unmodelled longitudinal/lateral dynamics, uncertain load conditions, uncertain communication conditions among the UAVs, and other uncertain factors.
Within this PhD thesis we develope novel adaptive and distributed guidance approaches for fixed-wing UAVs. The following three aspects are studied:
* Vector field guidance under uncertainties
* Distributed formation control with uncertain UAV dynamics
* Testing in the real world to achieve Sim-to-Real transfer