Periodic Energy-Optimal Path Planning for Solar-Powered Aircraft

Spangelo, Sara; Gilbert, Éric; Klesh, Andrew T.; Kabamba, Pierre T.; Girard, Anouck

doi:10.2514/6.2009-6016

Cited by 35 publications

(25 citation statements)

References 24 publications

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“…The position of the sun plays an important role in the amount of energy collected. This model is more formally presented in [15]. If a and e are the azimuth and elevation angles of the sun respectively, then the input φ , the bank angle of the aircraft, is related to the incidence angle i as…”

Section: The Energy Collection Modelmentioning

confidence: 99%

Trajectory Design and Coverage Control for Solar-Powered UAVs

Vasisht

Mesbahi

2015

AIAA Guidance, Navigation, and Control Conference

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This paper explores the benefits and challenges of using solar energy to power unmanned aerial vehicles (UAVs) for surveillance purposes. The task of persistent surveillance requires constant supply of input energy and is of particular significance in a number of applications such as weather monitoring, wildfire control, pollution or contamination detection, target search and other long endurance missions. Here, we consider the task of monitoring a geographical area for events of varying priorities and design optimal trajectories for sufficient continuous coverage of the region and eliminate the need to devise a refueling policy. Trajectories are designed based on how the UAVs collect the solar energy to carry out the mission under a variety of dynamic and endurance constraints. An algorithm is proposed to handle the energy collection and the coverage of the target area. Different goals are set and simulation results are presented to demonstrate the ability of the UAVs to meet these goals.

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Section: The Energy Collection Modelmentioning

confidence: 99%

Trajectory Design and Coverage Control for Solar-Powered UAVs

Vasisht

Mesbahi

2015

AIAA Guidance, Navigation, and Control Conference

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“…The sun position is however assumed constant. Spangelo [37] investigates optimal climb and descent maneuvers during loitering. Hosseini [20] adds sun-position time dependence, but assumes perfect clear-sky conditions instead of considering meteorological data.…”

Section: State Of the Artmentioning

confidence: 99%

Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Solar-Powered Aircraft

Oettershagen

Förster

Wirth

et al. 2019

Journal of Aerospace Information Systems

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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 4000 km Atlantic crossing from Newfoundland to Portugal, and two multi-glacier aerial inspection missions above the Arctic Ocean performed near Greenland in summer 2017. It is shown that integrating meteorological data has significant advantages and is indispensable for the reliable execution of large-scale solar-powered aircraft missions. For example, the correct selection of launch date and flight path across the Atlantic Ocean decreases the required flight time from 106 hours to only 52 hours.

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“…Other fixed-wing UAV path planning applications published in the literature include following coastlines [23], target localization [3], and energy conservation for solar powered vehicles [24], among many others.…”

Section: B Uav Path Planningmentioning

confidence: 99%

Sensor-Driven Area Coverage for an Autonomous Fixed-Wing Unmanned Aerial Vehicle

Paull

Thibault

Nagaty

et al. 2014

IEEE Trans. Cybern.

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Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are more appropriate for larger scale area surveying since they can cover ground more quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage a challenging task. Most previous approaches to area coverage planning are offline and assume that the UAV can follow the planned trajectory exactly. In this paper, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft is able to plan paths in situ based on sensor data and an accurate model of the on-board camera used for coverage. An information theoretic approach is used that selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept previously developed for autonomous underwater vehicles is extended to UAVs and ensures that the vehicle is able to achieve its global coverage mission. The coverage map over the workspace uses the projective camera model and compares the expected area of the target on the ground and the actual area covered on the ground by each pixel in the image. The camera is mounted on a two-axis gimbal and can either be stabilized or optimized for maximal coverage. Hardware-in-the-loop simulation results and real hardware implementation on a fixed-wing UAV show the effectiveness of the approach. By including the already developed automatic takeoff and landing capabilities, we now have a fully automated and robust platform for performing aerial imagery surveys.

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Periodic Energy-Optimal Path Planning for Solar-Powered Aircraft

Cited by 35 publications

References 24 publications

Trajectory Design and Coverage Control for Solar-Powered UAVs

Trajectory Design and Coverage Control for Solar-Powered UAVs

Meteorology-Aware Multi-Goal Path Planning for Large-Scale Inspection Missions with Solar-Powered Aircraft

Sensor-Driven Area Coverage for an Autonomous Fixed-Wing Unmanned Aerial Vehicle

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