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Sensorial Testbed for High-Voltage Tower Inspection with UAVs

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ROBOT2022: Fifth Iberian Robotics Conference (ROBOT 2022)

Abstract

This work presents a methodology for characterizing ultrasonic and LASER sensors aimed at detecting obstacles within the context of electrical inspections by multirotor Unmanned Aerial Vehicles (UAVs). A set of four ultrasonic and LASER sensor models is evaluated against eight target components, typically found in high-voltage towers. The results show that ultrasonic sensor arrays displaced 25\(^\circ \) apart reduce the chances of problems related to crosstalk and angular uncertainty. Within the LASER sensor suite, solar exposure directly affects the detection behavior among lower power sensors. Based on the results obtained, a set of sensors capable of detecting multiple obstacles belonging to a high-voltage tower was identified. In this reasoning, it becomes possible to model sensor architectures for multirotor UAVs to detect multiple obstacles and advance in the state of the art in obstacle avoidance systems by UAVs in inspections of high-voltage towers.

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Acknowledgment

The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020), SusTEC (LA/P/0007/2021), Oleachain “Skills for sustainability and innovation in the value chain of traditional olive groves in the Northern Interior of Portugal” (Norte06-3559-FSE-000188) and Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ). The project that gave rise to these results received the support of a fellowship from “la Caixa” Foundation (ID 100010434). The fellowship code is LCF/BQ/DI20/11780028.

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Correspondence to Guido S. Berger .

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Berger, G.S. et al. (2023). Sensorial Testbed for High-Voltage Tower Inspection with UAVs. In: Tardioli, D., Matellán, V., Heredia, G., Silva, M.F., Marques, L. (eds) ROBOT2022: Fifth Iberian Robotics Conference. ROBOT 2022. Lecture Notes in Networks and Systems, vol 590. Springer, Cham. https://doi.org/10.1007/978-3-031-21062-4_29

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  • DOI: https://doi.org/10.1007/978-3-031-21062-4_29

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  • Online ISBN: 978-3-031-21062-4

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