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Authors: Ronnier Rohrich 1 ; Luis Messias 1 ; Jose Lima 2 ; 3 and Andre Schneider de Oliveira 1

Affiliations: 1 Graduate School of Electrical Engineering and Computer Science, Universidade Tecnológica Federal do Paraná (UTFPR), Curitiba, Brazil ; 2 Research Centre in Digitalization and Intelligent Robotics (Cedri), Polytechnic Institute of Bragança (IPB), Bragança, Portugal ; 3 Institute for Systems and Computer Engineering of Porto, INESC-TEC, Porto, Portugal

Keyword(s): Mobile Robot, Olfactory Robotics, Linear Regression.

Abstract: This work addresses the problem of gas leaks and proposes a search strategy for identifying the source of a gas leak within a virtual simulation environment. The research focuses on designing and implementing simulation, control, and gas source search packages using swarm robotics. The simulation employs numerical integration strategies, while the robot swarm control is based on potential fields theory. The location of the gas source using a weighted linear regression strategy is used to estimate the gas concentration gradient, which plays a crucial role in the optimization strategy employed. The paper presents an overview of the key concepts employed and their relevance to different stages of the problem and highlights the main results achieved through the chosen strategies. A significant outcome of this work is the development of reusable software packages applicable to various research contexts in mobile robotics.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Rohrich, R.; Messias, L.; Lima, J. and Schneider de Oliveira, A. (2023). A Linear Regression Based-Approach to Collective Gas Source Localization. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5; ISSN 2184-2809, SciTePress, pages 657-664. DOI: 10.5220/0012187100003543

@conference{icinco23,
author={Ronnier Rohrich. and Luis Messias. and Jose Lima. and Andre {Schneider de Oliveira}.},
title={A Linear Regression Based-Approach to Collective Gas Source Localization},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={657-664},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012187100003543},
isbn={978-989-758-670-5},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - A Linear Regression Based-Approach to Collective Gas Source Localization
SN - 978-989-758-670-5
IS - 2184-2809
AU - Rohrich, R.
AU - Messias, L.
AU - Lima, J.
AU - Schneider de Oliveira, A.
PY - 2023
SP - 657
EP - 664
DO - 10.5220/0012187100003543
PB - SciTePress