Automated Environmental Stewardship: A Ribbon-Cutting Robot with Machine Vision for Sustainable Operation

Biplov Paneru; Bishwash Paneru; Ramhari Poudyal; Krishna Bikram Shah; Khem Narayan Poudyal; Yam Krishna Poudel

doi:10.35882/teknokes.v17i1.679

Biplov Paneru Department of Electronics & Communication Engineering, Nepal Engineering College Pokhara University, Bhaktapur, NEPAL https://orcid.org/0000-0003-2003-0648
Bishwash Paneru Department of Applied Science Engineering, Tribhuvan University, Kathmandu, NEPAL https://orcid.org/0009-0000-4025-2542
Ramhari Poudyal Department of Electrical Engineering, Purbanchal University, Biratnagar, NEPAL https://orcid.org/0000-0003-1853-7765
Krishna Bikram Shah Department of Computer Science and Engineering, Nepal Engineering College Pokhara University, Bhaktapur, NEPAL https://orcid.org/0000-0003-1763-511X
Khem Narayan Poudyal Department of Applied Science Engineering, Tribhuvan University, Kathmandu, NEPAL https://orcid.org/0000-0002-0890-1933
Yam Krishna Poudel Department of Electronics & Communication Engineering, Nepal Engineering College Pokhara University, Bhaktapur, NEPAL https://orcid.org/0000-0002-9438-0395

DOI: https://doi.org/10.35882/teknokes.v17i1.679

Keywords: Robot, Color Detection , Tensorflow, Keras

Abstract

This paper provides a novel way for automating ribbon-cutting rituals that use a specifically constructed robot with superior computer vision capabilities. The system achieves an outstanding 92% accuracy rate when assessing picture data by using a servo motor for ribbon identification, a motor driver for robot movement control, and nichrome wire for precision cutting. The robot's ability to recognize and interact with the ribbon is greatly improved when it uses a Keras and TensorFlow-based red ribbon identification model which obtained accuracy of about 93% on testing set before deployment in system. Implemented within a Raspberry Pi robot, the method exhibits amazing success in automating ceremonial activities, removing the need for human intervention. This multidisciplinary method assures the precision and speed of ribbon-cutting events, representing a significant step forward in the merging of tradition and technology via the seamless integration of robots and computer vision.

Downloads

Download data is not yet available.

References

Sathyamoorthy, S. Umapathy and T. Rajalakshmi, "Automatic Robotic Arm Based on Bluetooth Regulated for Progressed Surgical Task," 2022 International Conference on Industry 4.0 Technology (I4Tech), Pune, India, 2022, pp. 1-4, doi: 10.1109/I4Tech55392.2022.9952598.

Paneru, B. (2023). Development of a Ribbon Cutting Robot Controlled via Bluetooth Interface. Retrieved from https://www.techrxiv.org/articles/preprint/Development_of_a_Ribbon_Cutting_Robot_Controlled_via_Bluetooth_Interface/24305851. doi: 10.36227/techrxiv.24305851.v1

Baumgartner, Eric & Skaar, Steven. (1994). An autonomous vision-based mobile robot. Automatic Control, IEEE Transactions on. 39. 493 - 502. 10.1109/9.280748.

Chuprov, S.; Belyaev, P.; Gataullin, R.; Reznik, L.; Neverov, E.; Viksnin, I. Robust Autonomous Vehicle Computer-Vision-Based Localization in Challenging Environmental Conditions. Appl. Sci. 2023, 13, 5735. https://doi.org/10.3390/app13095735

Kumer, S.V. Aswin, Nadipalli, L.S.P. Sairam, Kanakaraja, P., Kumar, K. Sarat, & Sri Kavya, K.Ch. (2021). Controlling the autonomous vehicle using computer vision and cloud server. Materials Today: Proceedings, 37(2), 2982-2985. ISSN 2214-7853. https://doi.org/10.1016/j.matpr.2020.08.712.

R. Brooks, "A robust layered control system for a mobile robot," in IEEE Journal on Robotics and Automation, vol. 2, no. 1, pp. 14-23, March 1986, doi: 10.1109/JRA.1986.1087032.

F. Pfeiffer and R. Johanni, "A concept for manipulator trajectory planning," in IEEE Journal on Robotics and Automation, vol. 3, no. 2, pp. 115-123, April 1987, doi: 10.1109/JRA.1987.1087090.

Pedre, Sol & Nitsche, Matias & Pessacg, Facundo & Caccavelli, Javier & De Cristóforis, Pablo. (2014). Design of a Multi-purpose Low-Cost Mobile Robot for Research and Education. 10.1007/978-3-319-10401-0_17.

Fortuna, L., Ikpeze, O., Ejidokun, T., & Onibonoje, M. (2022). Smartphone Control Mobile Robot for Education and Research. Journal of Robotics, 2022, 5178629. https://doi.org/10.1155/2022/5178629

Wang, J. J. (2020). Design and Research of Intelligent Mobile Robot Based on IOT Information Fusion. In International Conference on Advances in Biological Science and Technology (pp. 012003). IOP Conf. Series: Earth and Environmental Science, 470. IOP Publishing. doi:10.1088/1755-1315/470/1/012003.

Kumar, Rahul & Kubade, Pravin & Kulkarni, Hrushikesh. (2016). Android Phone controlled Bluetooth Robot.

H. O. Nasereddin, Hebah. (2010). SMARTPHONE CONTROL ROBOTS THROUGH BLUETOOTH. International Journal of Research and Reviews in Applied Sciences. 4. 399-404.

Rissanen, Heikki & Mahonen, Jukka & Haataja, Keijo & Johansson, Markus & Mielikainen, Jarno & Toivanen, Pekka. (2009). Designing and implementing an intelligent Bluetooth-enabled robot car. 2009 IFIP International Conference on Wireless and Optical Communications Networks, WOCN 2009. 1 - 6. 10.1109/WOCN.2009.5010563.

Chapala, Sai. (2021). Color Detection of RGB Images Using Python and OPENCV. International Journal for Research in Applied Science and Engineering Technology. 9. 1957-1959. 10.22214/ijraset.2021.37701.

Neves, António & Trifan, Alina & Azevedo, José & Cunha, Bernardo. (2016). Real-Time Color Coded Object Detection Using a Modular Computer Vision Library. Advances in Computer Science. 5. 110-123.

Shahria, M.T.; Sunny, M.S.H.; Zarif, M.I.I.; Ghommam, J.; Ahamed, S.I.; Rahman, M.H. A Comprehensive Review of Vision-Based Robotic Applications: Current State, Components, Approaches, Barriers, and Potential Solutions. Robotics 2022, 11, 139. https://doi.org/10.3390/robotics11060139

T. Senlet and A. Elgammal, "Design of a vision-based autonomous robot for street navigation," 2014 22nd Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 2014, pp. 862-865, doi: 10.1109/SIU.2014.6830366.

L. Milburn, J. Gamba, M. Fernandes and C. Semini, "Computer-Vision Based Real Time Waypoint Generation for Autonomous Vineyard Navigation with Quadruped Robots," 2023 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Tomar, Portugal, 2023, pp. 239-244, doi: 10.1109/ICARSC58346.2023.10129563.

S. Shafique, S. Abid, F. Riaz and Z. Ejaz, "Computer Vision based Autonomous Navigation in Controlled Environment," 2021 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan, 2021, pp. 1-6, doi: 10.1109/ICRAI54018.2021.9651414.

Bengtson, S.H.; Thøgersen, M.B.; Mohammadi, M.; Kobbelgaard, F.V.; Gull, M.A.; Andreasen Struijk, L.N.S.; Bak, T.; Moeslund, T.B. Computer Vision-Based Adaptive Semi-Autonomous Control of an Upper Limb Exoskeleton for Individuals with Tetraplegia. Appl. Sci. 2022, 12, 4374. https://doi.org/10.3390/app12094374

Rostami, S.M.H., Sangaiah, A.K., Wang, J. et al. "Real-time obstacle avoidance of mobile robots using state-dependent Riccati equation approach." J Image Video Proc. 2018, 79 (2018). https://doi.org/10.1186/s13640-018-0319-1

Müller, Julian & Fregin, Andreas & Dietmayer, Klaus. (2018). "Disparity Sliding Window: Object Proposals From Disparity Images."

Ng, Andrew. (2004). "Feature selection, L 1 vs. L 2 regularization, and rotational invariance." Proceedings of the Twenty-First International Conference on Machine Learning. 10.1145/1015330.1015435.

Gurkov, Igor and Gurkov, Igor. "Making a Mundane Ceremony Into a Meaningful Organizational Ritual –Some Suggestions for Re-Design of Ribbon-Cutting Ceremonies of Overseas Manufacturing Projects." Available at SSRN: https://ssrn.com/abstract=3676716 or http://dx.doi.org/10.2139/ssrn.3676716

S, Sathiyamoorthy. (2014). "INDUSTRIAL APPLICATION OF MACHINE VISION." International Journal of Research in Engineering and Technology. Volume: 03. 10.15623/ijret.2014.0319120.

Li, R.; Zhao, S.; Yang, B. "Research on the Application Status of Machine Vision Technology in Furniture Manufacturing Process." Appl. Sci. 2023, 13, 2434. https://doi.org/10.3390/app13042434

A. O. Fernandes, L. F. E. Moreira and J. M. Mata. "Machine vision applications and development aspects." 2011 9th IEEE International Conference on Control and Automation (ICCA), Santiago, Chile, 2011, pp. 1274-1278, doi: 10.1109/ICCA.2011.6138014.

Xiao ZF, Wang JL, Han L, Guo SB and Cui QH. "Application of Machine Vision System in Food Detection." Front. Nutr. 9:888245. doi: 10.3389/fnut.2022.888245

Conrad, J.; Rodriguez, S.; Omidvarkarjan, D.; Ferchow, J.; Meboldt, M. "Recognition of Additive Manufacturing Parts Based on Neural Networks and Synthetic Training Data: A Generalized End-to-End Workflow." Appl. Sci. 2023, 13, 12316. https://doi.org/10.3390/app132212316

Zhang, Chen & Xu, Xuewu & Fan, Chen & Wang, Guoping. (2021). "Literature Review of Machine Vision in Application Field." E3S Web of Conferences. 236. 04027. 10.1051/e3sconf/202123604027.