Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft
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....
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ftdatacite:10.48550/arxiv.1711.10328 2023-05-15T15:09:49+02:00 Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft Oettershagen, Philipp Förster, Julian Wirth, Lukas Ambühl, Jacques Siegwart, Roland 2017 https://dx.doi.org/10.48550/arxiv.1711.10328 https://arxiv.org/abs/1711.10328 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Robotics cs.RO Artificial Intelligence cs.AI FOS Computer and information sciences Preprint Article article CreativeWork 2017 ftdatacite https://doi.org/10.48550/arxiv.1711.10328 2022-04-01T10:20:29Z 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. Report Arctic Arctic Ocean glacier Greenland Newfoundland DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean Greenland |
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DataCite Metadata Store (German National Library of Science and Technology) |
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Robotics cs.RO Artificial Intelligence cs.AI FOS Computer and information sciences |
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Robotics cs.RO Artificial Intelligence cs.AI FOS Computer and information sciences Oettershagen, Philipp Förster, Julian Wirth, Lukas Ambühl, Jacques Siegwart, Roland Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft |
topic_facet |
Robotics cs.RO Artificial Intelligence cs.AI FOS Computer and information sciences |
description |
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. |
format |
Report |
author |
Oettershagen, Philipp Förster, Julian Wirth, Lukas Ambühl, Jacques Siegwart, Roland |
author_facet |
Oettershagen, Philipp Förster, Julian Wirth, Lukas Ambühl, Jacques Siegwart, Roland |
author_sort |
Oettershagen, Philipp |
title |
Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft |
title_short |
Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft |
title_full |
Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft |
title_fullStr |
Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft |
title_full_unstemmed |
Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Long-Endurance Solar-Powered Aircraft |
title_sort |
meteorology-aware multi-goal path planning for large-scale inspection missions with long-endurance solar-powered aircraft |
publisher |
arXiv |
publishDate |
2017 |
url |
https://dx.doi.org/10.48550/arxiv.1711.10328 https://arxiv.org/abs/1711.10328 |
geographic |
Arctic Arctic Ocean Greenland |
geographic_facet |
Arctic Arctic Ocean Greenland |
genre |
Arctic Arctic Ocean glacier Greenland Newfoundland |
genre_facet |
Arctic Arctic Ocean glacier Greenland Newfoundland |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.1711.10328 |
_version_ |
1766340926234427392 |