Design and Fabrication of an Arduino-Based 5-DoF Robotic Arm for Pick-and-Place Applications
Keywords:
robotic arm, pick-and-place, Arduino UNO, servo motor, automation, 5-DoF, Bluetooth control
Abstract
The design, construction, control, and performance assessment of an Arduino-based, five-degree-of-freedom robotic arm intended for pick-and-place tasks are presented in this work. Using acrylic structural elements, six AD002 servo motors, an Arduino UNO R3 microcontroller, an Adept driver board, and Bluetooth-based control via an Android interface, the prototype was created as an inexpensive educational and testing platform. With consideration for payload capacity, structural stability, and convenience of use, the system was set up to offer synchronised motion at the base, shoulder, elbow, wrist, and gripper joints. Following assembly and calibration, three objects weighing 0.0245 kg, 0.0297 kg, and 0.0347 kg were used to test the robotic arm over a predetermined distance of 0.061 m. Higher payloads required more actuator effort and longer completion times, but the arm successfully finished all pick-and-place trials. The outcomes demonstrated that the system maintained adequate stability and repeatability during testing and operated dependably under modest loads. In addition to pointing up possibilities for future development in cargo handling, structural strengthening, and motion efficiency, the study shows that a basic microcontroller-based robotic arm can function as an efficient model for robotics education, embedded control, and small-scale automation.
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Abdelmajied, F. Y. (2022). Industry 4.0 and its implications: Concept, opportunities, and future directions. In Supply Chain-Recent Advances and New Perspectives in the Industry 4.0 Era. IntechOpen.
Aheleroff, S., Huang, H., Xu, X., & Zhong, R. Y. (2022). Toward sustainability and resilience with Industry 4.0 and Industry 5.0. Frontiers in Manufacturing Technology, 2, 951643.
Allam, K. (2022). Big data analytics in robotics: Unleashing the potential for intelligent automation. EPH-International Journal of Business & Management Science, 8(4), 5–9.
Alzarok, H., Fletcher, S., & Longstaff, A. P. (2020). Survey of the current practices and challenges for vision systems in industrial robotic grasping and assembly applications. Advances in Industrial Engineering and Management, 9(1), 19–30.
Andreoni, A., & Anzolin, G. (2020). A revolution in the making? Challenges and opportunities of digital production technologies for developing countries.
Arden, N. S., Fisher, A. C., Tyner, K., Lawrence, X. Y., Lee, S. L., & Kopcha, M. (2021). Industry 4.0 for pharmaceutical manufacturing: Preparing for the smart factories of the future. International Journal of Pharmaceutics, 602, 120554.
Baratta, A., Cimino, A., Longo, F., & Nicoletti, L. (2023). Digital twin for human-robot collaboration enhancement in manufacturing systems: Literature review and direction for future developments. Computers & Industrial Engineering, 109764.
Berx, N., Decré, W., Morag, I., Chemweno, P., & Pintelon, L. (2022). Identification and classification of risk factors for human-robot collaboration from a system-wide perspective. Computers & Industrial Engineering, 163, 107827.
Bonci, A., Cen Cheng, P. D., Indri, M., Nabissi, G., & Sibona, F. (2021). Human-robot perception in industrial environments: A survey. Sensors, 21(5), 1571.
Brogårdh, T. (2007). Present and future robot control development: An industrial perspective. Annual Reviews in Control, 31(1), 69–79.
Burrus, D. (2026, April 6). Best robotics companies to watch in 2026. https://www.burrus.com/articles/best-robotics-companies/
Butt, J. (2020). A strategic roadmap for the manufacturing industry to implement Industry 4.0. Designs, 4(2), 11.
Campilho, R. D., & Silva, F. J. (2023). Industrial process improvement by automation and robotics. Machines, 11(11), 1011.
Ciliberto, C., Szopik-Depczyńska, K., Tarczyńska-Łuniewska, M., Ruggieri, A., & Ioppolo, G. (2021). Enabling the circular economy transition: A sustainable lean manufacturing recipe for Industry 4.0. Business Strategy and the Environment, 30(7), 3255–3272.
Coronado, E., Yamanobe, N., & Venture, G. (2023). NEP+: A human-centered framework for inclusive human-machine interaction development. Sensors, 23(22), 9136.
Dixon, J., Hong, B., & Wu, L. (2021). The robot revolution: Managerial and employment consequences for firms. Management Science, 67(9), 5586–5605.
Duan, S., Shi, Q., & Wu, J. (2022). Multimodal sensors and ML-based data fusion for advanced robots. Advanced Intelligent Systems, 4(12), 2200213.
Dzedzickis, A., Subačiūtė-Žemaitienė, J., Šutinys, E., Samukaitė-Bubnienė, U., & Bučinskas, V. (2021). Advanced applications of industrial robotics: New trends and possibilities. Applied Sciences, 12(1), 135.
ElMaraghy, H., Monostori, L., Schuh, G., & ElMaraghy, W. (2021). Evolution and future of manufacturing systems. CIRP Annals, 70(2), 635–658.
Fucile, P., David, V. C., Kalogeropoulou, M., Gloria, A., & Moroni, L. (2024). RAVEN: Development of a novel robotic additive manufacturing system towards small-scale fabrication of complex scaffolds for regenerative medicine. Rapid Prototyping Journal, 30(10), e2410412. https://doi.org/10.1080/17452759.2024.2410412
Franke, A., Nass, E., Piereth, A. K., Zettl, A., & Heidl, C. (2021). Implementation of assistive technologies and robotics in long-term care facilities: A three-stage assessment based on acceptance, ethics, and emotions. Frontiers in Psychology, 12, 694297.
George, A. S., & George, A. H. (2023). The cobot chronicles: Evaluating the emergence, evolution, and impact of collaborative robots in next-generation manufacturing. Partners Universal International Research Journal, 2(2), 89–116.
Gökalp, M. O., Gökalp, E., Kayabay, K., Koçyiğit, A., & Eren, P. E. (2021). Data-driven manufacturing: An assessment model for data science maturity. Journal of Manufacturing Systems, 60, 527–546.
Jerman, A., Pejić Bach, M., & Aleksić, A. (2020). Transformation towards smart factory system: Examining new job profiles and competencies. Systems Research and Behavioral Science, 37(2), 388–402.
Javaid, M., Haleem, A., Singh, R. P., Rab, S., & Suman, R. (2022). Significant applications of cobots in the field of manufacturing. Cognitive Robotics, 2, 222–233.
Kim, S. (2022). Working with robots: Human resource development considerations in human–robot interaction. Human Resource Development Review, 21(1), 48–74.
Lages, L. F., Ricard, A., Hemonnet-Goujot, A., & Guerin, A. M. (2020). Frameworks for innovation, collaboration, and change: Value creation wheel, design thinking, creative problem-solving, and lean. Strategic Change, 29(2), 195–213.
Lee, N. C. A., Wang, E. T., & Grover, V. (2022). IOS drivers of interface with integrated multimodal sensing. International Journal of Advanced Multidisciplinary Research and Studies.
Li, H., & Li, Y. (2025). Finite element analysis and structural optimization design of multifunctional robotic arm for garbage truck. Frontiers in Mechanical Engineering, 11, 1543967. https://doi.org/10.3389/fmech.2025.1543967
Mahajan, R. G., Ansari, M. I., Sayyad, F. B., Kolekar, U. N., Dixit, P. A., Unde, S., & Allampallewar, G. (2025). Theoretical and experimental investigation on direct kinematic of pick and place 4R robotic arm using algebraic and software approach. International Journal on Interactive Design and Manufacturing, 19, 3259–3265. https://doi.org/10.1007/s12008-024-01884-1
MIT News. (2024, August 8). A new model offers robots precise pick-and-place solutions. https://news.mit.edu/2024/new-model-offers-robots-precise-pick-place-solutions-0809
Ranjan, V., Vullingala, D. S. K., Polamarasetti, S. K., Gunupuru, K. K., & Tompa, M. (2024). Exploring robotic arm fabrication: An in-depth review of current trends. Journal of Control & Instrumentation, 15(3), 28–41.
Vagdevi, L. L., & Harshitha, E. (2025). Development of robotic arm using Arduino. International Journal of Scientific Research & Engineering Trends.
Zhang, S., Liu, T., Li, X., Cai, C., Chang, C., & Xue, X. (2025). Key technologies of robotic arms in unmanned greenhouse. Agronomy, 15(11), 2498. https://doi.org/10.3390/agronomy15112498
Published
2026-04-26
How to Cite
AMAKOROMO, T. E., & OKOYE, O. E. (2026). Design and Fabrication of an Arduino-Based 5-DoF Robotic Arm for Pick-and-Place Applications. European Journal of Science, Innovation and Technology, 6(2), 98-108. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/761
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