dc.creator | Anderson, Alejandro | es |
dc.creator | García Martín, Javier | es |
dc.creator | Bouraqadi, Noury | es |
dc.creator | Etienne, Lucien | es |
dc.creator | Maestre Torreblanca, José María | es |
dc.creator | Duviella, Éric | es |
dc.date.accessioned | 2023-12-11T13:40:54Z | |
dc.date.available | 2023-12-11T13:40:54Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Anderson, A., García Martín, J., Bouraqadi, N., Etienne, L., Maestre, J.M. y Duviella, É. (2022). Nonlinear Set-based Model Predictive Control for Exploration: Application to Environmental Missions. En Proceedings 19th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2022 (230-237), Lisboa: Science and Technology Publications, Lda. | |
dc.identifier.isbn | 978-989758585-2 | es |
dc.identifier.issn | 2184-2809 | es |
dc.identifier.uri | https://hdl.handle.net/11441/152361 | |
dc.description.abstract | Acquiring vast and reliable data of physicochemical parameters is critical to environment
monitoring. In the context of water quality analysis, data collection solutions have to overcome
challenges related to the scale of environments to be explored. Sites to monitor can be large or
remote. These challenges can be approached by the use of Unmanned Vehicles (UVs). Robots provide
both flexibility on intervention plans and technological methods for real-time data acquisition. Being
autonomous, UVs can explore areas difficult to access or far from the shore. This paper presents a
nonlinear Model Predictive Control (MPC) for UV-based exploration. The strategy aims to improve the
data collection of physicochemical parameters with the use of an Unmanned Surface Vehicle (USV)
targeting water quality analysis. We have performed simulations based on real field experiments with
a SPYBOAT® on the Heron Lake in Villeneuve d’Ascq, France. Numerical results suggest that the
proposed strategy outperforms the schedule of mission planning and exploration for large areas. | es |
dc.description.sponsorship | Departamento de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía PAIDI 2020 | es |
dc.format | application/pdf | es |
dc.format.extent | 9 p. | es |
dc.language.iso | eng | es |
dc.publisher | Science and Technology Publications, Lda | es |
dc.relation.ispartof | Proceedings 19th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2022 (2022), pp. 230-237. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Nonlinear MPC | es |
dc.subject | Unmanned Vehicles | es |
dc.subject | Environmental Missions | es |
dc.subject | Water Quality Assessment | es |
dc.title | Nonlinear Set-based Model Predictive Control for Exploration: Application to Environmental Missions | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.projectID | P18-HO-4713 | es |
dc.relation.publisherversion | https://www.scitepress.org/Link.aspx?doi=10.5220/0011307300003271 | es |
dc.identifier.doi | 10.5220/0011307300003271 | es |
dc.contributor.group | Universidad de Sevilla. TEP116: Automática y Robótica Industrial | es |
dc.publication.initialPage | 230 | es |
dc.publication.endPage | 237 | es |
dc.eventtitle | Proceedings 19th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2022 | es |
dc.eventinstitution | Lisboa | es |
dc.contributor.funder | Junta de Andalucía PAIDI 2020 | es |