Economical 3D-Printed Robotic Arm for Educational Training Purpose

Main Article Content

Budi Hadisujoto
Wahyu Nur Budiarta
Raffy Frandito
Kushendarsyah Saptaji
Farid Triawan
Djati Wibowo
Janice Ong

Abstract

The advancement of Engineering technology requires universities as the frontier to educate engineering students with the latest skillset. Fast progress of Artificial Intelligence (AI) shown by the recently released of open AI such as ChatGPT, Genius, etc., has opened a new trend of technological tools. Hence, it is necessary or it can be said a must to train future engineers how to at least use these tools. Robotics and automation have long been used to assist humans in manufacture, logistic, health, and many other areas. Implementing AI into robotics creates intelligent systems which are predicted to be widely used. However, for educational institutions, especially in developing countries, the cost to afford the training robot equipment is still pricy. Here, we present designing and building of an economical robotic arm using 3D printed parts and open sources. The robot arm has six Degrees of Freedoms (DoF) and capable of lifting about 450 grams of maximum load. Some suggestions include future development are presented.

Downloads

Download data is not yet available.

Article Details

How to Cite
Hadisujoto, B., Budiarta, W. N. ., Frandito, R., Saptaji, K., Triawan, F. ., Wibowo, D. ., & Ong, J. . (2025). Economical 3D-Printed Robotic Arm for Educational Training Purpose. Jurnal Teknologi, 17(2), 89–100. https://doi.org/10.24853/jurtek.17.2.89-100
Section
Articles

References

M. Xu, J. M. David, S.H. Kim, ”The Fourth Industrial Revolution: Opportunities and Challenges”, International Journal of Financial Research, Vol. 9, No. 2; 2018, https://doi.org/10.5430/ijfr.v9n2p90.

C. Chaka, “Fourth industrial revolution–a review of applications, prospects, and challenges for artificial intelligence, robotics and blockchain in higher education”, Research and Practice in Technology Enhanced Learning (RPTEL), Vol. 18, 002, 2023, https://doi.org/10.58459/rptel.2023.18002.

H. Lee, J. L. Enriquez, G. Lee, “Robotics 4.0 : Challenges and Opportunities in the 4th Industrial Revolution”, Journal of Internet Services and Information Security (JISIS), Vol. 12, No. , 2022, pp. 39-55. Available: https://www.researchgate.net/profile/John-Laurence-Enriquez/publication/366302410_Robotics_40_Challenges_and_Opportunities_in_the_4th_Industrial_Revolution/links/63a9764ba03100368a2e496b/Robotics-40-Challenges-and-Opportunities-in-the-4th-Industrial-Revolution.pdf

P. Papcun, J. Jadlovsky, “Optimizing Industry Robot for Maximum Speed with High Accuracy”, Procedia Engineering, Vol. 48, 2012, pp. 533-542, https://doi.org/10.1016/j.proeng.2012.09.550

A. Zihni, W. D. Gerull, J. A. Cavallo, T. Ge, S. Ray, J. Chiu, L. M. Brunt, M. M. Awad, ”Comparison of precision and speed in laparoscopic and robot-assisted surgical task performance”, Journal of Surgical Research, Vol. 223, 2018, pp29-33, https://doi.org/10.1016/j.jss.2017.07.037

A. Raina, C. McComb, J. Cagan, “Learning to Design From Humans: Imitating Human Designers Through Deep Learning”, Journal of Mechanical Design, Vol. 141, 11, 2019, https://doi.org/10.1115/1.4044256

J. Hua, L. Zeng, G. Li, Z. Ju, “Learning for a Robot: Deep Reinforcement Learning, Imitation Learning, Transfer Learning”, Sensors 2021, 21, 1278. https://dx.doi.org/10.3390/s21041278

A. K. B. Motaleb, M. B. Hoque, and Md. A. Hoque, “Bomb disposal robot,” 2016 International Conference on Innovations in Science, Engineering and Technology (ICISET), Oct. 2016, doi: https://doi.org/10.1109/iciset.2016.7856510.

B. Hadisujoto, A. N. Rabbani, K. Saptaji, N. K. Fernandez, D. Wibowo, “Development of 3D Printed Autonomous Warehouse Robot Using Mecanum Wheel and Robot Arm”, Journal of Applied Science and Advanced Technology (JASAT), Vol. 6, No. 2, 2023. Available: https://jurnal.umj.ac.id/index.php/JASAT/article/view/19244/10047

L. E. Alvarez-Dionisi, M. Mittra, R. Balza, “Teaching Artificial Intelligence and Robotics to Undergraduate Systems Engineering Students”, International Journal of Modern Education and Computer Science (IJMECS), 2019, 7, pp. 54-63. Available: https://www.mecs-press.org/ijmecs/ijmecs-v11-n7/IJMECS-V11-N7-6.pdf

R. Febrianto, Djukarna, I W. A. Saputra, A. Alfiansyah, Syafrudi, “ Designand Development of a 5-DOF SCARA Robot Arm for Robotic Education in a STEM Laboratory”, The Indonesian Journal of Computer Science (IJCS), Vol. 13,5, 2024, https://doi.org/10.33022/ijcs.v13i5.4373

A. R. A. Tahtawi, M. Agni, T. D. Hendrawati, “Small-scale RobotArm Designwith Pick and Place Mission Based on Inverse Kinematics”, Journal of Robotics and Control (JRC), Vol. 2, 6, 2021, https://journal.umy.ac.id/index.php/jrc/article/view/10699/5996

S. Jung, “Experiences in Developing an Experimental Robotics Course Program for Undergraduate Education,” IEEE Transactions on Education, Vol. 56, no. 1, pp. 129-136, 2013, doi: 10.1109/TE.2012.2213601. Available: https://ieeexplore.ieee.org/document/6297492

J. Iqbal, R. U. Islam, and H. Khan, “Modeling and analysis of a 6 DOF robotic arm manipulator,” vol. 3, no. 6, pp. 300–306, Jan. 2012, Available: https://www.researchgate.net/publication/280643085_Modeling_and_analysis_of_a_6_DOF_robotic_arm_manipulator

M. Rana and A. Roy, “Design and Construction of a Robotic Arm for Industrial Automation,” 2017. Available: https://www.ijert.org/research/design-and-construction-of-a-robotic-arm-for-industrial-automation-IJERTV6IS050539.pdf

K. L. Conrad, P. S. Shiakolas, T. C. Yih, “Robotic Calibration Issues: Accuracy, Repeatability and Calibration”, Proceedings of the 8th Mediterranean Conference on Control & Automation (MED 2000), Rio, Patras, GREECE, 17-19 July 2000. Available: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=343b9f29c959be50431aa8c07127bc52b0a1c522

I. Daniyan, K. Mpofu, B. Ramatsetse,A. Adeodu, “Design and simulation of a robotic arm for manufacturing operations in the railcar industry”, Procedia Manufacturing, Vol. 51, 2020, pp. 67-72. https://doi.org/10.1016/j.promfg.2020.10.011

P. I. Corke, "A Simple and Systematic Approach to Assigning Denavit–Hartenberg Parameters," IEEE Transactions on Robotics, Vol. 23, No. 3, pp. 590-594, 2007, doi: 10.1109/TRO.2007.896765. Available: https://ieeexplore.ieee.org/document/4252158

S. Hernandez-Mendez, C. Maldonado-Mendez, A. Marin-Hernandez, H. V. Rios-Figueroa, H. Vazquez-Leal and E. R. Palacios-Hernandez, "Design and implementation of a robotic arm using ROS and MoveIt!," 2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), Ixtapa, Mexico, 2017, pp. 1-6, doi: 10.1109/ROPEC.2017.8261666. Available: https://ieeexplore.ieee.org/abstract/document/8261666

S. Pachaiyappan, M. Micheal Balraj, and T. Sridhar3, “Design and Analysis of an Articulated Robot Arm for Various Industrial Application”, IOSR Journal of Mechanical and Civil Engineering, 2014, pp.42-53. Available: https://www.iosrjournals.org/iosr-jmce/papers/NCCAMABS/Volume-1/7.pdf

C. Rasmussen, “How to Easily Calculate Gear Ratios in Planetary Systems,” Mentored Engineer, 2021. Available: https://mentoredengineer.com/calculate-planetary-gear-ratios/

M. Sulaiman, M. I. K. Syaffiq, A. Said, H. N. M. Shah, M. N. Fakhzan, “Simulation and Experimental Work of Kinematic Problems for Kuka Kr 5 Sixx R650 Articulated Robot”, International Journal of Energy amd Power Engineering Research 1, 2013, pp.6-9. Available: https://www.academia.edu/download/74659740/SIMULATION_AND_EXPERIMENTAL_WORK_OF_KINE20211114-18468-bwekph.pdf

Most read articles by the same author(s)