Gyroscope and Accelerometer Sensor on the Lanange Jagad Dance Robot Balance System

Authors

  • Ahmad Sopi Samosir Ahmad Dahlan University
  • Nuryono Satya Widodo Ahmad Dahlan University

DOI:

https://doi.org/10.12928/biste.v2i2.922

Keywords:

Robot Humanoid, Accelerometer, Gyroscope, Kalman Filter, KRSTI

Abstract

In performing dance moves, humanoid robots are expected to move flexibly and not easily fall during dance moves. To reduce the risk of robots falling while performing dance moves, a balance control system using a gyroscope sensor and accelerometer from the MPU6050 is controlled through the Arduino MEGA 2560 PRO. Robots that have balance control, are able to maintain stability in track conditions that have a certain degree of slope. This balance control system uses the Kalman filter method for processing data from the gyroscope sensor and accelerometer in order to reduce the noise that occurs during the robot's balance process. From the results of the test, the percentage of the success rate of robots in rest was 88.8%, the percentage of success when the robot was running was 86.6%, and the percentage of success when the robot was walking with dancing was 75%. From the results of all tests, humanoid robot has a percentage of 83.4% after adding a balance control system and when the humanoid robot does not use balance control will only produce a percentage of success rate of 48.4%.

References

J. Pembangunan, P. : Fondasi, D. Aplikasi, M. Ngafifi, S. Negeri, and S. Wonosobo, “Kemajuan Teknologi dan Pola Hidup Manusia dalam Persperktif Sosial Bidaya,” Jurnal Pembangunan Pendidikan: Fondasi dan Aplikasi, vol. 2, no. 1, pp. 33–45, Jun. 2014.

A. I. Bardani and N. S. Widodo, “Deteksi Zona pada KRSTI dengan Sensor Warna TCS3200,” Buletin Ilmiah Sarjana Teknik Elektro, vol. 1, no. 2, p. 56, 2019.

S. Al Irfan and N. S. Widodo, “Application of Deep Learning Convolution Neural Network Method on KRSBI Humanoid R-SCUAD Robot,” Buletin Ilmiah Sarjana Teknik Elektro, vol. 2, no. 1, pp. 40–50, 2020.

I. Maulana and N. S. Widodo, “Sistem Pengolah Musik Sebagai Kontrol Gerak Robot Humanoid,” Buletin Ilmiah Sarjana Teknik Elektro, vol. 1, no. 2, p. 46, 2019.

S. Kajita, H. Hirukawa, K. Harada, and K. Yokoi, “Introduction to Humanoid Robotics,” in Introduction to Humanoid Robot, vol. 101, Springer Verlag, 2014.

R. Zahra, Thamrin, and P. Jaya, “Rancang Bangun Robot Humanoid Penari Gending Sriwijaya Menggunakan Modul EasyVR3,” Voteknika: Jurnal Teknik Elektronika dan Informatika, vol. 5, no. 2, pp. 129–137.

U. W. Putri and Thamrin, “Perancangan Pergerakan Kaki Robot Humanoid Menggunakan Servo Dynamixel OpenCM9.04,” Voteknika: Jurnal Teknik Elektronika dan Informatika, vol. 7, no. 3, pp. 76–84.

M. Kumagai and T. Ochiai, “Development of a robot balancing on a ball,” in 2008 International Conference on Control, Automation and Systems, ICCAS 2008, 2008, pp. 433–438.

M. Ismail, R. A. Dziyauddin, and N. A. A. Salleh, “Performance evaluation of wireless accelerometer sensor for water pipeline leakage,” 2016, pp. 120–125.

A. Maarif, R. D. Puriyanto, and F. R. T. Hasan, “Robot Keseimbangan dengan Kendali PID dan Kalman Filter,” IT JOURNAL RESEARCH AND DEVELOPMENT, vol. 4, no. 2, Feb. 2020.

Z. Liang, H. Zhao, and Y. Hao, “An omnidirectional walk for a biped robot based on gyroscope-accelerometer measurement,” in 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014, 2014, pp. 1052–1057.

A. S. Ilmi and M. Muslihudin, “Sistem Klasifikasi Otomatis Volume Balok dengan Arduino,” Buletin Ilmiah Sarjana Teknik Elektro, vol. 1, no. 1, p. 9, 2019.

K. Kunal, A. Z. Arfianto, J. E. Poetro, F. Waseel, and R. A. Atmoko, “Accelerometer Implementation as Feedback on 5 Degree of Freedom Arm Robot,” Journal of Robotics and Control (JRC), vol. 1, no. 1, pp. 31–34, 2020.

A. Ma’arif, I. Iswanto, A. A. Nuryono, and R. I. Alfian, “Kalman Filter for Noise Reducer on Sensor Readings,” Signal and Image Processing Letters, vol. 1, no. 2, pp. 11–22, Jul. 2019.

S. Yuliani and H. M. Saputra, “Kolaborasi Kalman Filter dengan Complementary Filter untuk Mengoptimasi Hasil Sensor Gyroscope dan Accelerometer Reengineering Software Data Logger Triaxial Digital View project Modified Fourth-Order Runge-Kutta Method Based on Trapezoid Approach View pro,” in Prosiding Seminar Nasional Rekayasa dan Desain Itenas, 2016, pp. 63–68.

G. Welch and G. Bishop, “An Introduction to the Kalman Filter,” 1995.

M. S. Grewal and A. P. Andrews, Kalman Filtering: Theory and Practice with MATLAB. Wiley, 2015.

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Published

2020-08-30

How to Cite

[1]
A. S. Samosir and N. S. Widodo, “Gyroscope and Accelerometer Sensor on the Lanange Jagad Dance Robot Balance System”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 2, no. 2, pp. 51–58, Aug. 2020.

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