UAV fleet mission planning subject to robustness constraints

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

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (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.

Original languageEnglish
Title of host publicationDistributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference, DCAI 2020
EditorsSara Rodríguez González, Javier Prieto, Alfonso González-Briones, Arkadiusz Gola, George Katranas, Michela Ricca, Roussanka Loukanova, Roussanka Loukanova
Number of pages13
PublisherSpringer
Publication date1 Jan 2021
Pages35-47
ISBN (Print)9783030538286
DOIs
Publication statusPublished - 1 Jan 2021
Event17th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2020 - L´Aquila, Italy
Duration: 17 Jun 202019 Jun 2020

Conference

Conference17th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2020
Country/TerritoryItaly
CityL´Aquila
Period17/06/202019/06/2020
SeriesAdvances in Intelligent Systems and Computing
Volume1242 AISC
ISSN2194-5357

Keywords

  • UAV fleet mission planning
  • UAV routing and scheduling

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