UAV Mission Planning Resistant to Weather Uncertainty

Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather con...

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Main Authors: Amila Thibbotuwawa, Grzegorz Bocewicz, Grzegorz Radzki, Peter Nielsen, Zbigniew Banaszak
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/2/515
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author Amila Thibbotuwawa
Grzegorz Bocewicz
Grzegorz Radzki
Peter Nielsen
Zbigniew Banaszak
author_facet Amila Thibbotuwawa
Grzegorz Bocewicz
Grzegorz Radzki
Peter Nielsen
Zbigniew Banaszak
author_sort Amila Thibbotuwawa
collection DOAJ
description Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning.
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spelling doaj.art-21a0000c66724060821b4ccea8e3538f2022-12-22T02:54:45ZengMDPI AGSensors1424-82202020-01-0120251510.3390/s20020515s20020515UAV Mission Planning Resistant to Weather UncertaintyAmila Thibbotuwawa0Grzegorz Bocewicz1Grzegorz Radzki2Peter Nielsen3Zbigniew Banaszak4Department of Materials and Production, Aalborg University, 9220 Aalborg, DenmarkFaculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, PolandFaculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, PolandDepartment of Materials and Production, Aalborg University, 9220 Aalborg, DenmarkFaculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, PolandFleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning.https://www.mdpi.com/1424-8220/20/2/515unmanned aerial vehiclesuav routing and schedulinguav fleet mission planning
spellingShingle Amila Thibbotuwawa
Grzegorz Bocewicz
Grzegorz Radzki
Peter Nielsen
Zbigniew Banaszak
UAV Mission Planning Resistant to Weather Uncertainty
Sensors
unmanned aerial vehicles
uav routing and scheduling
uav fleet mission planning
title UAV Mission Planning Resistant to Weather Uncertainty
title_full UAV Mission Planning Resistant to Weather Uncertainty
title_fullStr UAV Mission Planning Resistant to Weather Uncertainty
title_full_unstemmed UAV Mission Planning Resistant to Weather Uncertainty
title_short UAV Mission Planning Resistant to Weather Uncertainty
title_sort uav mission planning resistant to weather uncertainty
topic unmanned aerial vehicles
uav routing and scheduling
uav fleet mission planning
url https://www.mdpi.com/1424-8220/20/2/515
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