2026-06-26T16:50:13Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/714402023-08-28T04:31:54Zcom_20.500.14352_14col_20.500.14352_15

Bordón Ruiz, Juan B. López Orozco, José Antonio Besada Portas, Eva 2023-06-22T10:42:14Z 2023-06-22T10:42:14Z 2022-04-05 1747-7778 10.1080/17477778.2022.2053311 https://hdl.handle.net/20.500.14352/71440 http://dx.doi.org/10.1080/17477778.2022.2053311 https://www.tandfonline.com/ This paper presents a new Cloud-deployable DEVS-based framework for optimising UAV trajectories and sensor strategies in target-search missions. DEVS provides it with a well-established, flexible, and verifiable modelling strategy to include different models for the UAV, sensor, and target dynamics; the target and sensor uncertainty; and the optimising process. Its Cloud deployability speeds up the evaluations/simulations required to optimise this NP-hard problem, which involves computationally heavy models when solving real-world missions. The framework, designed to handle different types of target-search missions, currently optimises, using a multi-objective Genetic Algorithm, free-shape trajectories of multiple UAVs,eqquiped with several static/movable sensors to detect a target within a search area. It is implemented in xDEVS and deployable over a set of containers in the Google Cloud Platform. The results show that our deployment policy speeds up the computation up to 3.35 times, letting the operator simultaneously optimise several search strategies for agiven scenario. eng https://creativecommons.org/licenses/by-nc/3.0/es/ open access Atribución-NoComercial 3.0 España Cloud DEVS-based computation of UAVs trajectories for search and rescue missions journal article