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Authors: José Mário Nishihara de Albuquerque and Ronnier Rohrich

Affiliation: Graduate School of Electrical Engineering and Computer Science, Universidade Tecnológica Federal do Paraná (UTFPR), Curitiba, Brazil

Keyword(s): LiDAR, Inspection, Autonomous Robot, Power Lines.

Abstract: This article presents a novel technique using Light Detection and Ranging (LiDAR) sensors implemented in an autonomous robot for the multimodal predictive inspection of high-voltage transmission lines (LaRa). The method enhances the robot’s capabilities by providing vertical perception and classifying transmission-line components using artificial-intelligence techniques. The LiDAR-based system focuses on analyzing two-dimensional (2D) slices of objects, reducing the data volume, and increasing the computational efficiency. Object classification was achieved by calculating the absolute differences within a 2D slice to create unique signatures. When evaluated experimentally with a k-nearest neighbors network on a Raspberry Pi on a real robot, the system accurately detected objects such as dampers, signals, and insulators during linear movement experiments. The results indicated that this approach significantly improves LaRa’s ability to recognize power-line components, achieving high c lassification accuracy and exhibiting potential for advanced autonomous inspection applications. (More)

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Paper citation in several formats:
Mário Nishihara de Albuquerque, J. and Rohrich, R. (2024). LiDAR-Based Object Recognition for Robotic Inspection of Power Lines. In Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-717-7; ISSN 2184-2809, SciTePress, pages 197-204. DOI: 10.5220/0012985800003822

@conference{icinco24,
author={José {Mário Nishihara de Albuquerque} and Ronnier Rohrich},
title={LiDAR-Based Object Recognition for Robotic Inspection of Power Lines},
booktitle={Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2024},
pages={197-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012985800003822},
isbn={978-989-758-717-7},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - LiDAR-Based Object Recognition for Robotic Inspection of Power Lines
SN - 978-989-758-717-7
IS - 2184-2809
AU - Mário Nishihara de Albuquerque, J.
AU - Rohrich, R.
PY - 2024
SP - 197
EP - 204
DO - 10.5220/0012985800003822
PB - SciTePress

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