Abstract
This paper proposes a methodology to visual assist a robotic arm to accurately micro-localize different optoelectronic components by means of object detection and recognition techniques. The various image processing tasks performed for the effective guidance of the robotic arm are analyzed under the scope of implementing a specific production scenario with localization accuracy in the scale of a few microns, proposed by a laser diode manufacturer. In order to elaborate the necessary procedures for achieving the required functionality, the required algorithms engaged in every step are presented. The analysis of possible implementations of the vision algorithms for achieving the required image recognition tasks take into account the possible content of the camera data, the accuracy of the results based on predefined specifications, as well as the computational complexity of the available algorithmic solutions.
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Acknowledgements
This work was supported by the 7th Framework Programme (FP7), FoF.NMP.2013-2: Innovative Re-Use of Modular Equipment Based on Integrated Factory Design, in the context of the WhiteR project under Grant GA609228. All vision related hardware components were provided by Framos GmbH.
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Theoharatos, C., Kastaniotis, D., Besiris, D., Fragoulis, N. (2018). Vision-Based Mapping and Micro-localization of Industrial Components in the Fields of Laser Technology. In: Esposito, A., Faudez-Zanuy, M., Morabito, F., Pasero, E. (eds) Multidisciplinary Approaches to Neural Computing. Smart Innovation, Systems and Technologies, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-319-56904-8_23
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DOI: https://doi.org/10.1007/978-3-319-56904-8_23
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