UAV fleet mission planning subject to robustness constraints

G. Radzki, P. Nielsen, G. Bocewicz*, Z. Banaszak

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

1 Citationer (Scopus)

Abstract

Fleet mission planning for Unmanned Aerial Vehicles (UAVs) involves creating flight plans for a specific set of objectives, which typically, have to be achieved over a specific time period. The key challenge is to develop methods allowing to prototype mission plans, encompassing UAV routes and schedules, that are robust to changing weather conditions and energy constraints. This paper presents a declarative approach to solving UAV mission planning problems subject to weather uncertainty. The approach was tested using several examples, for which we analyzed how the achievement of mission goals depended on parameters, such as UAV fleet size, UAV energy capacity, weather changes, including wind direction and wind speed, as well as the structure of the distribution network and the time horizon.

OriginalsprogEngelsk
TitelDistributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference, DCAI 2020
RedaktørerSara Rodríguez González, Javier Prieto, Alfonso González-Briones, Arkadiusz Gola, George Katranas, Michela Ricca, Roussanka Loukanova, Roussanka Loukanova
Antal sider13
ForlagSpringer
Publikationsdato1 jan. 2021
Sider35-47
ISBN (Trykt)9783030538286
DOI
StatusUdgivet - 1 jan. 2021
Begivenhed17th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2020 - L´Aquila, Italien
Varighed: 17 jun. 202019 jun. 2020

Konference

Konference17th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2020
Land/OmrådeItalien
ByL´Aquila
Periode17/06/202019/06/2020
NavnAdvances in Intelligent Systems and Computing
Vol/bind1242 AISC
ISSN2194-5357

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