Long-Endurance Sensing and Mapping using a Hand-Launchable Solar-Powered UAV

ISSN:1610-743

Solar-Powered Unmanned Aerial Vehicles: Design and Environment-Aware Navigation for Robust Low-Altitude Multi-Day Continuous Flight

The multi-day continuous flight capability of solar-powered Unmanned Aerial Vehicles (UAVs) can be of significant benefit in large-scale aerial sensing missions such as search-and-rescue support, border patrol and industrial or agricultural inspection. However, today these UAVs suffer from small payload capacity, low energetic safety margins and high operational complexity. This cumulative doctoral thesis therefore contributes models, design methods and algorithmic frameworks which improve the energetic robustness, ease of use and versatility of low-altitude solar-powered perpetual flight-capable UAVs. The thesis follows an applications-driven approach and therefore also presents first real-life missions in complex environments. The first part of this thesis discusses modeling, design and flight testing of solar-powered perpetual-flight-capable UAVs. We contribute energetic system models and a novel formal conceptual design methodology with a derived design software to devise solar-powered UAVs for energetically-robust perpetual flight in suboptimal meteorological conditions. Our design approach is applied to AtlantikSolar, a small hand-launchable 7 kg perpetual-flight-capable solar UAV. The detailed airframe, power system, propulsion and avionics design is described. In addition, we present simple yet robust attitude estimation and flight control approaches which are specifically optimized for the challenging flight dynamics of solar UAVs. Finally, a novel extended Kalman filter-based method for fully autonomous tracking of thermal updrafts is presented: In contrast to solely vertical-velocity based estimation approaches, it improves the problem’s observability by fusing the thermal-induced roll moment measurement. It is therefore especially suitable for solar UAVs given their large wing span. Extensive flight campaigns demonstrate the effectiveness of the contributions. First, AtlantikSolar’s continuous 81.5 h (4 days and 3 nights) and 2338km solar-powered flight, which broke the world record in flight endurance for all aircraft below 50 kg mass, is presented. The minimum battery state of charge during the night is increased from the 10% of previous UAV designs to 39% for AtlantikSolar. A significant increase in the energetic robustness to deteriorated weather is thus achieved. The results indicate that AtlantikSolar allows perpetual flight in a 6-month window around June 21st at mid-European latitudes and throughout the whole year at latitudes smaller than 27°. Second, the first-ever fully-automated multi-day flight of a low-altitude solar UAV with a day/night-capable sensing payload is presented: This 26-hour search-and rescue mockup mission is also the first-ever combined use of solar-electric propulsion and autonomous thermal updraft tracking. The fact that the flight did not require a single pilot intervention demonstrates the improved ease of use of the developed aerial system. The second part of this thesis covers algorithms for the environment-aware navigation of UAVs. We present two frameworks: First, the Meteorology-aware Trajectory Planning and Analysis Software for Solar-powered UAVs. MetPASS is the first planning framework in the literature that considers a system model, the terrain, and all meteorological effects that are of importance for typically fragile solar UAVs (e.g. thunderstorms, rain, winds, clouds) and can therefore plan safe and cost-optimal routes even for remote missions in complex environments. MetPASS is leveraged to plan a hypothetical Atlantic crossing with AtlantikSolar. It is also employed to both plan and execute AtlantikSolar’s 81-hour world record flight and its first real-life mission, a large-scale 230km glacier scanning operation above the Arctic Ocean near Greenland. MetPASS however performs all its computations offline on a ground-based computer. In contrast, the second contribution covers online environment-aware navigation: A real-time wind-aware sampling-based path planner is developed and combined with initial work on the first-ever 3D wind field prediction method that can run directly onboard a UAV. The potential-field-based wind prediction is verified with 1D LIDAR data. While the vertical wind errors are still significant, the overall wind error is reduced by 23% with respect to a zero-wind assumption that is mostly used in small-scale UAV path planning today. Together, the planner and wind prediction framework provide an initial basis for real-time fully environment-aware navigation in cluttered terrain and complex wind fields. Overall, as demonstrated with the first real-life mission in remote Arctic terrain, the presented algorithms significantly increase the versatility of solar-powered UAVs. This thesis concludes with the remaining research challenges and a suggested way forward towards more real-life missions with perpetual-flight-capable solar-powered UAVs