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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI: | http://purl.tuc.gr/dl/dias/6AA57E77-4D1D-409C-BA3E-90BD40A82892 | ||
| Year | 2022 | ||
| Type of Item | Conference Full Paper | ||
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| Bibliographic Citation | K. Moirogiorgou, F. Raptopoulos, G. Livanos, S. Orfanoudakis, M. Papadogiorgaki, M. Zervakis and M. Maniadakis, "Intelligent robotic system for urban waste recycling," in Proceedings of the 2022 IEEE International Conference on Imaging Systems and Techniques (IST 2022), Kaohsiung, Taiwan, 2022, doi: 10.1109/IST55454.2022.9827769. https://doi.org/10.1109/IST55454.2022.9827769 | ||
| Appears in Collections |
Urban waste management is a most challenging issue for modern societies. Reducing pollution and saving environmental resources provides significant opportunities for local, national and international economic growth. In Greece, the recycling rates are currently low compared to other European countries. The current study proposes an autonomous, intelligent robotic system for categorizing and separating recyclable materials aiming to contribute in increasing the recycling rates in Greece. The system is a series connection of an optical sub-system and a robotic sub-system. The optical subsystem receives input from a ordinary RGB and an NIR camera. These are processed in combination for the identification and categorization of recyclables into predefined material types. The output of the optical sub-system provides a list of potential targets (recyclables) to be picked and sorted. This is forwarded to the robotic subsystem, which undertakes the physical separation of the materials to the appropriate bin. The proposed system, named ANASA system, has been deployed in two different urban waste management industrial units, in DEDISA, Chania, Crete, Greece (processing recyclable wastes) and in ESDAK, Heraklion, Crete, Greece (processing composite wastes), where the system's reliability and validity is experimentally tested in real industrial environments. The advantages over the existing ordinary recycling systems are significant: high reliability in object recognition (material detection), short separation cycle (high speed), significantly low installation volume, low cost and ease of application to both old and new recycling industries. The combination of the above features provides a potential for exploitation as a complete commercial commercialization.
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