Analysis of Lifting Load Current on Trainable Robot Arm Based on Arduino Mega 2560
Keywords:
Arduino Mega 2560, Trainable Robot, Load Current, Robotic ArmAbstract
The rapid advancement of robotics has significantly influenced industrial automation, education, and research. Among the most studied systems is the robotic arm, which mimics human arm movements and can be programmed for repetitive and precision tasks. This study focuses on the analysis of lifting load current in a trainable robotic arm controlled by an Arduino Mega 2560 microcontroller. The main objective is to investigate the current consumption of servo motors under various load conditions, ranging from 50 g to 500 g, and to identify the optimal operating range. The methodology employed includes system design, hardware implementation, current measurement using sensors, and experimental validation under incremental load variations. Results indicate a linear correlation between the lifted load and current consumption, with 400 g identified as the maximum safe load at 0.72 A. Beyond this threshold, motor overheating and vibrations were observed. The findings contribute to the design of energy-efficient robotic arms, optimal actuator selection, and safe operational guidelines for educational and industrial applications.
References
M. Asada and H. Hosoda, “Cognitive developmental robotics,” IEEE Trans. Auton. Ment. Dev., vol. 1, no. 1, pp. 19–34, 2009.
T. Zhang, Y. Wang, and K. Li, “Applications of robotic arms in smart manufacturing,” IEEE Access, vol. 7, pp. 102345–102356, 2019.
A. Kumar, “Arduino microcontroller in educational robotics,” Int. J. Adv. Res. Electr. Electron. Instrum. Eng., vol. 4, no. 5, pp. 502–508, 2015.
A. T. Jones and L. Peters, “Servo motor analysis for robotic systems,” in Proc. IEEE Int. Conf. Robotics and Automation, 2018, pp. 1354–1359.
D. Wu and J. Luo, “Thermal performance of servo motors under variable load,” IEEE Trans. Ind. Electron., vol. 63, no. 8, pp. 5125–5133, 2016.
J. Smith and A. Brown, “Arduino-based robotic arm for education,” Int. J. Robotics Res., vol. 35, no. 4, pp. 321–329, 2020.
P. Kumar and R. Gupta, “Design of low-cost trainable robot arm,” in Proc. IEEE CASE, 2018, pp. 123–128.
L. Chen, M. Zhao, and T. Wu, “Analysis of servo motor current in robotic applications,” IEEE Trans. Ind. Electron., vol. 66, no. 5, pp. 4123–4131, May 2019.
H. A. Hassan, “Performance evaluation of Arduino-based robotic systems,” J. Mechatronics Autom., vol. 12, no. 2, pp. 87–94, 2019.
S. Yadav and V. Sharma, “Load analysis of robotic servo motors,” IEEE Access, vol. 8, pp. 22445–22454, 2020.
Hutapea, Marshal, Mhd Erpandi Dalimunthe, And Yuliarman Saragih. "Rancang
Bangun Trainable Robot Arm Berbasis Arduino Mega 2560 Sebagai Media Praktikum
Di Laboratorium Teknik Elektro Universitas Pembangunan Pancabudi Medan." Aisyah
Journal Of Informatics And Electrical Engineering (Ajiee) 6.2 (2024): 151-159.
Sulistyono, Eko. Kendali Lengan Robot Berbasis Android Untuk Otomasi Lifting
Barang. MS thesis. Universitas Islam Sultan Agung (Indonesia), 2021.
Muhardiansyah, Rahmaniar, and M. Erpandi Dalimunthe, “Wireless Sensor Network
Performance Analysis for Indoor Air Quality Monitoring”, ICDSET, pp. 523–534, Jun.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Muhammad Erpandi Dalimunthe, Marshal Warisman Hutapea
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
International Conference On Islamic Community Studies, Education and Science, its website, and the articles published therein are licensed under a 
