Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring

UAVs used in monitoring crop fields are flying higher than 6 meters and capture telemetric data that provides information on the general condition of the plants in the field. But, in order to obtain specific information on the actual conditions of the plants based on individual morphological aspects...

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Main Authors: De Ocampo, Anton Louise P., Bandala, Argel A., Dadios, Elmer P.
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Published: Animo Repository 2018
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/646
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-16452022-02-02T00:32:40Z Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring De Ocampo, Anton Louise P. Bandala, Argel A. Dadios, Elmer P. UAVs used in monitoring crop fields are flying higher than 6 meters and capture telemetric data that provides information on the general condition of the plants in the field. But, in order to obtain specific information on the actual conditions of the plants based on individual morphological aspects, lower altitude monitoring, at most 3 meters, is required. Low-altitude missions cover less than high-altitude and requires UAVs to fly longer to cover more area. In this paper, an approach for multi-depot, fuel constrained coverage path planning is presented. First, target coverage is segmented into smaller regions based on the number of available charging depots. Then, each region is further decomposed into multitude of cells with area equivalent to the camera FOV when UAV is flying at 3 meters above the field. All possible routes are generated and fed into evolutionary optimization in aim to identify the optimal path considering the fuel constraints and availability of recharging depots. The optimization yields a significant improvement in obtaining the route that will provide the minimum distance that the UAV should traverse to cover the entire Area-of-Interest. This approach proved to be useful for crop field monitoring using UAVs. © 2018 IEEE. 2018-07-02T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/646 Faculty Research Work Animo Repository Drone aircraft Agricultural instruments Agricultural innovations Electrical and Computer Engineering Electrical and Electronics
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Drone aircraft
Agricultural instruments
Agricultural innovations
Electrical and Computer Engineering
Electrical and Electronics
spellingShingle Drone aircraft
Agricultural instruments
Agricultural innovations
Electrical and Computer Engineering
Electrical and Electronics
De Ocampo, Anton Louise P.
Bandala, Argel A.
Dadios, Elmer P.
Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring
description UAVs used in monitoring crop fields are flying higher than 6 meters and capture telemetric data that provides information on the general condition of the plants in the field. But, in order to obtain specific information on the actual conditions of the plants based on individual morphological aspects, lower altitude monitoring, at most 3 meters, is required. Low-altitude missions cover less than high-altitude and requires UAVs to fly longer to cover more area. In this paper, an approach for multi-depot, fuel constrained coverage path planning is presented. First, target coverage is segmented into smaller regions based on the number of available charging depots. Then, each region is further decomposed into multitude of cells with area equivalent to the camera FOV when UAV is flying at 3 meters above the field. All possible routes are generated and fed into evolutionary optimization in aim to identify the optimal path considering the fuel constraints and availability of recharging depots. The optimization yields a significant improvement in obtaining the route that will provide the minimum distance that the UAV should traverse to cover the entire Area-of-Interest. This approach proved to be useful for crop field monitoring using UAVs. © 2018 IEEE.
format text
author De Ocampo, Anton Louise P.
Bandala, Argel A.
Dadios, Elmer P.
author_facet De Ocampo, Anton Louise P.
Bandala, Argel A.
Dadios, Elmer P.
author_sort De Ocampo, Anton Louise P.
title Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring
title_short Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring
title_full Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring
title_fullStr Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring
title_full_unstemmed Coverage path planning on multi-depot, fuel constraint UAV missions for smart farm monitoring
title_sort coverage path planning on multi-depot, fuel constraint uav missions for smart farm monitoring
publisher Animo Repository
publishDate 2018
url https://animorepository.dlsu.edu.ph/faculty_research/646
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