Abstract
The creation and management of an intelligent waste sorting system using a robot arm are described in the study. This system comprises a 6DOF robot manipulator, a machine vision block, and a control unit for rubbish sorting using analytic pictures. The item will be recognized by the neural network using the YOLOv4 software. This technique detects and identifies various types and kinds of trash, including paper-based waste, metal waste, and plastic waste. Results of offline testing on a library of more than 600 untrained photos reveal that the trained model has an average classification accuracy of roughly 98.43%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Poon, C., Ann, T., Ng, L.: On-site sorting of construction and demolition waste in Hong Kong. Resour. Conserv. Recycl. 32(2), 157172 (2001)
Ahmad, S.: A new technology for automatic identification and sorting of plastics for recycling. Environ. Technol. 25(10), 1143–1149 (2004)
Huang, J., Pretz, T., Bian, Z.: Intelligent solid waste processing using optical sensor based sorting technology, in image and signal. In: Processing (CISP), 2010 3rd International Congress on, IEEE, vol 4, pp 1657–1661 (2010)
Lukka, T.J., Tossavainen, T., Kujala, J.V., Raiko, T.: Zenrobotics recyclerrobotic sorting using machine learning. In: Proceedings of the International Conference on Sensor-Based Sorting (SBS) (2014)
Paulraj, S.G., Hait, S., Thakur, A.: Automated municipal solid waste sorting for recycling using a mobile manipulator. In: ASME 2016, International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, pp. V05AT07A045V05AT07A045 (2016)
Kiyokawa, T., Katayama, H., Ogasawara, T.: Robotic waste sorter with agile manipulation and quickly trainable detector. In: Computer Science IEEE Access (2021)
Ang, F., Gabriel, M.K.A.R., Sy, J., Tan, J.J.O., Abad, A.C.: Automated waste sorter with mobile robot delivery waste system. In: de la salle University Research Congress, p. 79 (2013)
Russel, M.H., Chowdhury, M.H., Uddin, M.S.N., Newaz, A., Talukder, M.M.M.: Development of automatic smart waste sorter machine. In: Conference: International Conference on Mechanical, Industrial and Materials Engineering 2013 (ICMIME2013) (2013)
Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., Berg, A.C.: SSD: Single shot multibox detector. In: Proceeding of European Conference on Computer Vision, pp 21–37. Springer, New York (2016)
Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: Unified, real -time object detection. In: Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, pp 779–788 (2016)
Girshick R (2015) Fast R –CNN. In: Proceedings of IEEE International Conference on Computer Vision, pp 1440–1448
Halstead, M., McCool, C., Denman, S., Perez, T., Fookes, C.: Fruit quantity and quality estimation using a robotic vision system (2018). arXiv:1801.05560v1[cs.CV]
Zhang, J., Gao, G., Karkee, M., Zhang, X., He, L., Zhang, Q.: Branch detection for apple trees trained in fruiting wall architecture using depth features and regions -convolutional neural network (R -CNN). Comput Electron Agric 155, 386–393 (2018)
Diya1, S.Z., Proma, R.A., Islam, M.N., Anannya, T.T., Al Mamun, A., Arefeen, R,, Al Mamun, S,, Rahman, I.I., Rabbi, M.F.: Developing an intelligent waste sorting system with robotic arm: a step towards green environment. In: International Conference on Innovation in Engineering and Technology (ICIET) (2018)
Kiyokawa, T., Katayama, H., Tatsuta, Y., Takamatsu, J., Ogasawara, T.: Robotic waste sorter with agile manipulation and quickly trainable detector. IEEE Access 9 (2021)
Zhang, Z., Wang, H., Song, H., Zhang, S., Zhang, J.: Industrial robot sorting system for municipal solid waste ICIRA 2019: In: Intelligent Robotics and Applications. Industrial Robot Sorting System for Municipal Solid Waste, pp. 342–353
Gao, M., Cai, Q., Zheng, B., Shi, J.: A hybrid YOLO v4 and particle filter based robotic arm grabbing system in nonlinear and non-gaussian environment. Electronics 10(10), 1140 (2021)
https://github.com/Harighs/Robot-Arm-for-Sorting-Mechanism-using-ROS-and-YOLOv4
Acknowledgements
This research is sponsored by the project at the University of Economics - Technology for Industries, and University of Transport and Communications.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ha, V.T., Thuong, T.T., Ha, V.T. (2023). Developing an Intelligent Waste Sorting with 6DOF Robotic Arm. In: Nguyen, D.C., Vu, N.P., Long, B.T., Puta, H., Sattler, KU. (eds) Advances in Engineering Research and Application. ICERA 2022. Lecture Notes in Networks and Systems, vol 602. Springer, Cham. https://doi.org/10.1007/978-3-031-22200-9_44
Download citation
DOI: https://doi.org/10.1007/978-3-031-22200-9_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-22199-6
Online ISBN: 978-3-031-22200-9
eBook Packages: EngineeringEngineering (R0)