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Nonlinear Set-based Model Predictive Control for Exploration: Application to Environmental Missions

Topics: Engineering Applications; Engineering Applications on Intelligent Control Systems and Optimization; Engineering Applications on Robotics and Automation; Guidance, Navigation and Control; Modeling, Analysis and Control of Discrete-Event Systems; Planning and Scheduling; Quality Control and Management; Real-Time Systems Control; Robot Design, Development and Control; Systems Modeling and Simulation; Systems Modeling and Simulation; Vehicle Control Applications

Authors: A. Anderson 1 ; 2 ; J. M. Martin 3 ; N. Bouraqadi 1 ; L. Etienne 1 ; K. Langueh 1 ; L. Rajaoarisoa 1 ; G. Lozenguez 1 ; L. Fabresse 1 ; J. G. Maestre 3 and E. Duviella 1

Affiliations: 1 IMT Nord Europe, Institut Mines-Télécom, Centre for Digital Systems, F-59000 Lille, France ; 2 Instituto de Desarrollo Tecnológico para la Industria Química (INTEC), Consejo Nacional de Investigaciones Científicas y Tecnicas (CONICET), Santa Fe, Argentina ; 3 Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla, C/ Camino de los Descubrimientos, s/n., 41092 Sevilla, Spain

Keyword(s): Nonlinear MPC, Unmanned Vehicles, Environmental Missions, Water Quality Assessment.

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 outper forms the schedule of mission planning and exploration for large areas. (More)

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Paper citation in several formats:
Anderson, A., Martin, J. M., Bouraqadi, N., Etienne, L., Langueh, K., Rajaoarisoa, L., Lozenguez, G., Fabresse, L., Maestre, J. G. and Duviella, E. (2022). Nonlinear Set-based Model Predictive Control for Exploration: Application to Environmental Missions. In Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - ICINCO; ISBN 978-989-758-585-2; ISSN 2184-2809, SciTePress, pages 230-237. DOI: 10.5220/0011307300003271

@conference{icinco22,
author={A. Anderson and J. M. Martin and N. Bouraqadi and L. Etienne and K. Langueh and L. Rajaoarisoa and G. Lozenguez and L. Fabresse and J. G. Maestre and E. Duviella},
title={Nonlinear Set-based Model Predictive Control for Exploration: Application to Environmental Missions},
booktitle={Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - ICINCO},
year={2022},
pages={230-237},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011307300003271},
isbn={978-989-758-585-2},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - ICINCO
TI - Nonlinear Set-based Model Predictive Control for Exploration: Application to Environmental Missions
SN - 978-989-758-585-2
IS - 2184-2809
AU - Anderson, A.
AU - Martin, J.
AU - Bouraqadi, N.
AU - Etienne, L.
AU - Langueh, K.
AU - Rajaoarisoa, L.
AU - Lozenguez, G.
AU - Fabresse, L.
AU - Maestre, J.
AU - Duviella, E.
PY - 2022
SP - 230
EP - 237
DO - 10.5220/0011307300003271
PB - SciTePress

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