Unmanned Solar Airplanes: Design and Algorithms for Efficient and Robust Autonomous Operation

Solar airplanes offer the unique capability of staying airborne for extremely long times: to date, both unmanned and manned systems have proved sustained flight, in the sense of flying through several day and night cycles. During the day, the solar module powers the airplane and re-charges a battery, which must take the airplane through the following night. Small-scale unmanned solar airplanes have thus been suggested for a plethora of non-military application scenarios, ranging from disaster response to Search and Rescue (SaR) as well as general large-scale mapping missions. This thesis addresses many aspects related to long-term autonomous operation of this special class of Unmanned Aerial Systems (UAS) in close proximity to the ground. We start in the very beginning with asking the question of how large a solar airplane should be and how it would perform, in order to accomplish a target mission. A methodology is presented that performs actual aerodynamics and structural calculations of either a simplified shell or rib wing concept. The performance evaluation part also accounts for flying optimized altitude profiles, in order to allow for potential energy storage. The output of this conceptual design tool has motivated the design of the senseSoar solar airplane prototype that is equipped with enhanced sensing and processing components. We describe the details associated with the design of the different components—an engineering effort that spans various disciplines from aerodynamics to solar technology, electronics and avionics as well as structures. Furthermore, we introduce a modular sensing and processing unit that can be attached to a second solar airplane prototype, AtlantikSolar, aimed at record flying. The airplane was developed outside the scope of this work, but its realization was again motivated by the conceptual design tool. Throughout the design process, but also for subsequent simulations and autopilot development, aerodynamics and flight kinematics models play an important role; we present a complete toolchain for such analysis. Developing efficient components is key to any successful solar airplane design. Longterm operation, however, will only be enabled, if the aircraft additionally exhibits sufficient robustness. These two central concepts do not only apply to design, but equally to algorithms, which eventually turn the airplane into a system that can operate autonomously. As a basis for any autonomy, the aircraft needs to have an estimate about its internal states, as well as about its surroundings, specifically in the form of a map. Large parts of the thesis at hand address precisely the associated challenge of fusing various sensor sources under hard real-time and computational constraints. Specifically, two algorithms are presented and analyzed in detail that share a common element: namely inertial measurements, i.e. accelerometer and rate gyro readings subjected to their kinematics equations. A first fusion strategy complements this inertial module with magnetometer, static and dynamic pressure, as well as GPS measurements that are