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Applied Sciences
Volume 15
Issue 3
10.3390/app15031336
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Article

Integration of Deep Learning Vision Systems in Collaborative Robotics for Real-Time Applications

by
Nuno Terras
1,
Filipe Pereira
1,2,3,
António Ramos Silva
1,2,
Adriano A. Santos
2,4,
António Mendes Lopes
1,2,
António Ferreira da Silva
2,4,
Laurentiu Adrian Cartal
5,
Tudor Catalin Apostolescu
6,
Florentina Badea
7 and
José Machado
3,8,*
1
Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
2
INEGI-Institute of Science and Innovation in Mechanical and Industrial Engineering, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
3
MEtRICs Research Centre, School of Engineering, University of Minho, Campus of Azurém, 4800-058 Guimarães, Portugal
4
CIDEM-Department of Mechanical Engineering, School of Engineering, Polytechnic of Porto, Rua Dr. António Bernardino de Almeida 431, 4249-015 Porto, Portugal
5
Department of Mechatronics and Precision Mechanics, Faculty of Mechanical Engineering and Mechatronics, National University of Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania
6
Faculty of Informatics, Titu Maiorescu University, Calea Văcăreşti nr.189, Sector 4, 0400511 Bucharest, Romania
7
National Institute of Research and Development in Mechatronics and Measurement Technique, Șos. Pantelimon, Nr. 6-8, Sector 2, 021631 Bucharest, Romania
8
CESTER—Research Center for Industrial Robots Simulation and Testing, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(3), 1336; https://doi.org/10.3390/app15031336
Submission received: 26 December 2024 / Revised: 13 January 2025 / Accepted: 17 January 2025 / Published: 27 January 2025
(This article belongs to the Special Issue New Challenges in Conceptual Design of Robotic and Mechatronic Systems: 2nd Edition)
Versions Notes

Abstract

Collaborative robotics and computer vision systems are increasingly important in automating complex industrial tasks with greater safety and productivity. This work presents an integrated vision system powered by a trained neural network and coupled with a collaborative robot for real-time sorting and quality inspection in a food product conveyor process. Multiple object detection models were trained on custom datasets using advanced augmentation techniques to optimize performance. The proposed system achieved a detection and classification accuracy of 98%, successfully processing more than 600 items with high efficiency and low computational cost. Unlike conventional solutions that rely on ROS (Robot Operating System), this implementation used a Windows-based Python framework for greater accessibility and industrial compatibility. The results demonstrated the reliability and industrial applicability of the solution, offering a scalable and accurate methodology that can be adapted to various industrial applications.
Keywords: collaborative robots; computer vision; YOLO; deep learning; real-time object detection; industrial automation collaborative robots; computer vision; YOLO; deep learning; real-time object detection; industrial automation

Share and Cite

MDPI and ACS Style

Terras, N.; Pereira, F.; Ramos Silva, A.; Santos, A.A.; Lopes, A.M.; Silva, A.F.d.; Cartal, L.A.; Apostolescu, T.C.; Badea, F.; Machado, J. Integration of Deep Learning Vision Systems in Collaborative Robotics for Real-Time Applications. Appl. Sci. 2025, 15, 1336. https://doi.org/10.3390/app15031336

AMA Style

Terras N, Pereira F, Ramos Silva A, Santos AA, Lopes AM, Silva AFd, Cartal LA, Apostolescu TC, Badea F, Machado J. Integration of Deep Learning Vision Systems in Collaborative Robotics for Real-Time Applications. Applied Sciences. 2025; 15(3):1336. https://doi.org/10.3390/app15031336

Chicago/Turabian Style

Terras, Nuno, Filipe Pereira, António Ramos Silva, Adriano A. Santos, António Mendes Lopes, António Ferreira da Silva, Laurentiu Adrian Cartal, Tudor Catalin Apostolescu, Florentina Badea, and José Machado. 2025. "Integration of Deep Learning Vision Systems in Collaborative Robotics for Real-Time Applications" Applied Sciences 15, no. 3: 1336. https://doi.org/10.3390/app15031336

APA Style

Terras, N., Pereira, F., Ramos Silva, A., Santos, A. A., Lopes, A. M., Silva, A. F. d., Cartal, L. A., Apostolescu, T. C., Badea, F., & Machado, J. (2025). Integration of Deep Learning Vision Systems in Collaborative Robotics for Real-Time Applications. Applied Sciences, 15(3), 1336. https://doi.org/10.3390/app15031336

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