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Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/E4EDB338-B94A-42D0-A83E-E0AAF79C7284 | - |
| Identifier | https://doi.org/10.1109/ICUAS54217.2022.9836094 | - |
| Identifier | https://ieeexplore.ieee.org/document/9836094 | - |
| Language | en | - |
| Extent | 10 pages | en |
| Title | UAV path planning for offshore swarm-based missions | en |
| Creator | Platanitis Konstantinos | en |
| Creator | Πλατανιτης Κωνσταντινος | el |
| Creator | Kladis Georgios P. | en |
| Creator | Petrongonas Evangelos | en |
| Creator | Skliros Christos | en |
| Creator | Tsourveloudis Nikos | en |
| Creator | Τσουρβελουδης Νικολαος | el |
| Creator | Zagorianos Anastasios D. | en |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Description | This work is partially supported by Emerging indUstries new value chains boosted by small Flying Objects (UFO) project which received funding by the European Union’s Horizon 2020 research and innovation programme under grant agreement 873411, and by the Special Account for Research Funding the Technical University of Crete, under the grand codes 82238, 80309 and 81050/82273. | en |
| Content Summary | A key feature trend in Smart Delivery (SD) is the use of swarm robotics. In all swarm applications it is desirable that the group should be able to complete its goal(s) safely and energy efficiently, via a sophisticated decision making mechanism, whilst satisfying constraints and meeting mission’s requirements. This is one of the key objectives of the Artificial Intelligence Robust Offshore Unmanned System (AIROUS) project. In this article the offline swarm based Unmanned Aerial Vehicle (UAV) path planning problem is addressed for real offshore environments whilst enhancing energy requirements. A two-step procedure is adopted for the determination of the energy efficient safe-flyable route 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 and vessel traffic in a cluttered environment. By the latter step, those paths are fed in a Genetic Algorithm (GA) setup, to determine the best solution that fulfils the mission’s objectives. The efficacy of the approach is shown via simulation examples. | en |
| Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Full Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2024-10-11 | - |
| Date of Publication | 2022 | - |
| Subject | Energy efficiency | en |
| Subject | Genetic algorithm | en |
| Subject | Path planning | en |
| Subject | Swarm based missions | en |
| Bibliographic Citation | K. S. Platanitis, G. P. Kladis, E. Petrongonas, C. Skliros, N. C. Tsourveloudis and A. D. Zagorianos, "UAV path planning for offshore swarm-based missions," in Proceedings of the 2022 International Conference on Unmanned Aircraft Systems (ICUAS 2022), Dubrovnik, Croatia, 2022, pp. 124-133, doi: 10.1109/ICUAS54217.2022.9836094. | en |
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