  Solar-powered aircraft promise significantly increased flight endurance over
conventional aircraft. While this makes them promising candidates for
large-scale aerial inspection missions, their structural fragility necessitates
that adverse weather is avoided using appropriate path planning methods. This
paper therefore presents MetPASS, the Meteorology-aware Path Planning and
Analysis Software for Solar-powered UAVs. MetPASS is the first path planning
framework in the literature that considers all aspects that influence the
safety or performance of solar-powered flight: It avoids environmental risks
(thunderstorms, rain, wind, wind gusts and humidity) and exploits advantageous
regions (high sun radiation or tailwind). It also avoids system risks such as
low battery state of charge and returns safe paths through cluttered terrain.
MetPASS imports weather data from global meteorological models, propagates the
aircraft state through an energetic system model, and then combines both into a
cost function. A combination of dynamic programming techniques and an
A*-search-algorithm with a custom heuristic is leveraged to plan globally
optimal paths in station-keeping, point-to-point or multi-goal aerial
inspection missions with coverage guarantees. A full software implementation
including a GUI is provided. The planning methods are verified using three
missions of ETH Zurich's AtlantikSolar UAV: An 81-hour continuous solar-powered
station-keeping flight, a 4000km Atlantic crossing from Newfoundland to
Portugal, and two multi-glacier aerial inspection missions above the Arctic
Ocean performed near Greenland in summer 2017.
