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Safe flyable and energy efficient UAV missions via biologically inspired methods

Platanitis Konstantinos, Kladis Georgios P., Tsourveloudis Nikolaos

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URIhttp://purl.tuc.gr/dl/dias/EB9A9FDB-6F4E-4F75-BD1B-0D185A7DB070-
Αναγνωριστικόhttps://doi.org/10.1109/ICUAS48674.2020.9214038-
Αναγνωριστικόhttps://ieeexplore.ieee.org/document/9214038-
Γλώσσαen-
Μέγεθος10 pagesen
ΤίτλοςSafe flyable and energy efficient UAV missions via biologically inspired methodsen
ΔημιουργόςPlatanitis Konstantinosen
ΔημιουργόςΠλατανιτης Κωνσταντινοςel
ΔημιουργόςKladis Georgios P.en
ΔημιουργόςTsourveloudis Nikolaosen
ΔημιουργόςΤσουρβελουδης Νικολαοςel
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠερίληψηIn this article the offline Unmanned Aerial Vehicle (UAV) path planning problem is addressed for real environments whilst enhancing energy requirements. In particular, a two-step procedure is adopted for the determination of the energy efficient safe flyable path that satisfies a-priori defined criteria. By the former step, via principles of mechanics, safe flyable candidate paths are designed meeting functional/physical limitations of the aerial vehicle. By the latter step, those paths are fed in the Genetic Algorithm (GA) setup, and the best path that fulfils mission's objectives and satisfies constraints is determined. The efficacy of the approach is shown via simulation examples, where a UAV is deployed to safely navigate with the least energy demand in an a priori known environment whilst meeting mission objectives.en
ΤύποςΔημοσίευση σε Συνέδριοel
ΤύποςConference Publicationen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2022-12-14-
Ημερομηνία Δημοσίευσης2020-
Θεματική ΚατηγορίαGenetic algorithmsen
Θεματική ΚατηγορίαEnergy efficiencyen
Θεματική ΚατηγορίαUnmanned aerial vehiclesen
Θεματική ΚατηγορίαTrajectoryen
Θεματική ΚατηγορίαBiologyen
Θεματική ΚατηγορίαThree-dimensional displaysen
Βιβλιογραφική ΑναφοράK. S. Platanitis, G. P. Kladis and N. C. Tsourveloudis, "Safe flyable and energy efficient UAV missions via biologically inspired methods," 2020 International Conference on Unmanned Aircraft Systems (ICUAS), 2020, pp. 1868-1877, doi: 10.1109/ICUAS48674.2020.9214038.en

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