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An Advanced Robotic System Utilizing Convolutional Neural Networks for Recycling

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Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications (FAIEMA 2023)

Abstract

Computer vision-based path planning can play a crucial role in numerous technologically driven smart applications. The proposed computer vision-neural network technique was fed by two photographs that were taken from two separate vantage points in order to get accurate spatial coordinates of objects in real time. These photographs were shot from various angles. After that, Q-learning was utilized to build a set of fundamental operations, such as up, down, left, right, backward, and forward. These basic operations include moving up, down, left, and right, as well as forward and backward. In the end, a neural network that had been trained was used to find a set of joint angles that related to the activities that were detected. These angles were found by correlating the activities that were recognized with the joint angles.

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References

  • Cheng C, Lv X, Zhang J (2021) Robot arm path planning based on improved RRT algorithm. In: Proceedings of the 2021 3rd international symposium on robotics and intelligent manufacturing technology (ISRIMT). Changzhou, China

    Google Scholar 

  • Diya SZ, et al (2018) Developing an intelligent waste sorting system with robotic arm: a step towards green environment. In: 2018 international conference on innovation in engineering and technology (ICIET). Dhaka, Bangladesh, pp 1–6. https://doi.org/10.1109/CIET.2018.8660890

  • Gundupalli SP, Hait S, Thakur A (2017) A review on automated sorting of source-separated municipal solid waste for recycling. Waste Manage 60:56–74

    Google Scholar 

  • Kim J, Nocentini O, Scafuro M, Limosani R, Manzi A, Dario P, Cavallo F (2019) An innovative automated robotic system based on deep learning approach for recycling objects. In: ICINCO, vol 2, pp 613–622

    Google Scholar 

  • Lachi Reddy P, Sabiha S, Jaswitha K, et al (2021) Optimized garbage segregation and monitoring system. Mater Today Proc. https://doi.org/10.1016/J.MATPR.2021.07.256

  • Mondal S, Das S, Banerjee S, Pal K (2022) A smart automated garbage management system to replace human labour. In: 2022 6th international conference on devices, circuits and systems (ICDCS). Coimbatore, India, pp 1–5. https://doi.org/10.1109/ICDCS54290.2022.9780783

  • Municipal waste generation in EU. https://ec.europa.eu/eurostat/web/products-eurostat-news/-/DDN-20220214-4. Accessed on 21 June 2023

  • Satav AG, Kubade S, Amrutkar C, et al (2023) A state-of-the-art review on robotics in waste sorting: scope and challenges. Int J Interact Des Manuf. https://doi.org/10.1007/s12008-023-01320-w

  • Tsintotas KA, Bampis L, An S, Fragulis GF, Mouroutsos SG, Gasteratos A (2021) Sequence-based mapping for probabilistic visual loop-closure detection. In: 2021 IEEE international conference on imaging systems and techniques (IST). IEEE, pp. 1–6

    Google Scholar 

  • Tzounakos V, Maniadakis M, Autonomous robotic sorting of recyclable waste

    Google Scholar 

  • United States Environmental Protection Agency (2019) Recycling statistics. United States Environmental Protection Agency, Washington, D.C., USA

    Google Scholar 

  • World Bank. https://www.worldbank.org/en/topic/urbandevelopment/overview#1. Accessed 21 June 2023

  • Ziouzios D, Baras N, Balafas V, Dasygenis M, Stimoniaris A (2022) Intelligent and real-time detection and classification algorithm for recycled materials using convolutional neural networks. Recycling 7(1):9. https://doi.org/10.3390/recycling7010009

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Correspondence to Dimitris Ziouzios .

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Ziouzios, D., Chatzisavvas, A., Fragulis, G., Dasygenis, M. (2024). An Advanced Robotic System Utilizing Convolutional Neural Networks for Recycling. In: Farmanbar, M., Tzamtzi, M., Verma, A.K., Chakravorty, A. (eds) Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications. FAIEMA 2023. Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications. Springer, Singapore. https://doi.org/10.1007/978-981-99-9836-4_14

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