Abstract
Special Session: Hybrid and Convertible Unmanned Aerial Vehicles—Environments that have structures in multiple domains are a great challenge to performing inspection and monitoring tasks, often requiring several robots to perform in these ambient. Hybrid vehicles can become an alternative to the use of several devices. Especially, industrial marine ecosystems present a drastic change in the environment that can represent a challenge for these hybrid vehicles both in sensing and locomotion. Consequently, the use of infrared and acoustic sensors is discouraged for this particular vehicle type because they operate only in one specific medium. The infrared just works in air and acoustic sensor in the underwater environment, leading to limitations concerning weight for the vehicle’s structural development. Furthermore, the integration of both sensors adds complexity to the implementation of autonomy. This work presents a benchmark to evaluate the performance of visual sensors in both air and water showing its advantage and limitation.
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Acknowledgements
This study was financed by the Human Resource Program of The Brazilian National Agency for Petroleum, Natural Gas, and Biofuels—PRH-ANP, supported by resources from oil companies considering the contract clause n\(^{\underline{o}}\) 50/2015 of R, D &I of the ANP, CAPES, and CNPq. Moreover, we would like to thank to the Technological University of Uruguay (UTEC).
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Mateus, M.G. et al. (2024). Visual Sensors Benchmark for Development of an Autonomous Navigation Setup for a Hybrid Unmanned Aerial Underwater Vehicle. In: Youssef, E.S.E., Tokhi, M.O., Silva, M.F., Rincon, L.M. (eds) Synergetic Cooperation Between Robots and Humans. CLAWAR 2023. Lecture Notes in Networks and Systems, vol 810. Springer, Cham. https://doi.org/10.1007/978-3-031-47269-5_20
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