Abstract
The agility process used in Industry 4.0 increasingly influences on the location changes of the used production resources. Ensuring safety in a production environment is critical, especially when objects are moving or change their location e.g. transport trolleys, Autonomous Guided Vehicles or mobile robots. One of the methods of moving object discovery by other objects, e.g. AGV is application of distance sensors. Different sensors enable various measurement quality. In order to improve their accuracy, diverse calibration and filtration methods are often used. The article presents adaptive curve fitting method to increase accuracy of measurements for single-beam distance sensors. The research results of calibration were presented based on example of low cost ultrasounds and LiDARs sensors. Proposed adaptive curve fitting method enables to improve measurement accuracy even by 97%.
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Acknowledgements
The research leading to these results received funding from the Norway Grants 2014–2021, which is operated by the National Centre for Research and Development under the project “Automated Guided Vehicles integrated with Collaborative Robots for Smart Industry Perspective” (Project Contract no.: NOR/POLNOR/CoBotAGV/0027/2019 -00) and partially by the Statutory Research funds of the Department of Applied Informatics, Silesian University of Technology, Gliwice, Poland (grant No no BK-281/RAU8/2020).
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Biernacki, P., Ziębiński, A., Grzechca, D. (2021). The Adaptive Calibration Method for Single-Beam Distance Sensors. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_54
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