Center of Pressure Control for Balancing Humanoid Dance Robot Using Load Cell Sensor, Kalman Filter and PID Controller

Cisi Fitri Wulandari, Abdul Fadlil

Abstract


Balance control on the Lanage Jagad humanoid dance robot is one of the means to create flexible dance movements in the robot movement system to make it more stable and can reduce the frequency of the robot falling or being unable to maintain balance when performing the dance. For the position of the robot, it can use a weight sensor or load cell sensor, the sensor measures the resistance value that can control the weight of 4 weight points on each robot leg which will later be converted into a pressure value at each point, in the study. This test was carried out with the same control behavior using an inertial sensor MPU6050. The balance on the robot uses a balance based on a load cell, which is a situation where the position of the robot in coordinates approaches the center of balance or CoP (Center of Pressure) at coordinates (0,0) or if using MPU6050 it is in a far error value condition so that it can balance the conditions so as not to falls close to the value of the robot state based on ZMP (Zero Moment Point) and CoG (Central of Gravity) as the MPU6050 sensor placement. In this study, for the balance control system using the Arduino MEGA 2560 PRO Board as a complement to the OpenCM 9.04 microcontroller, using 8 load cell sensors to determine the balance point which has been made predictions of pressure from the load cell using a kalman filter also PID control to handle the servo motor. The results from the center point of the robot's pressure have succeeded in determining the center of balance or CoP based on the X coordinates of 0 and the Y coordinates of 0 and the quadrant direction based on the center of gravity, so that the results of the balance system in standing and dancing conditions are based on the center of balance using a load cell, the success rate when standing by 87.5% and balance when dancing by 89%.

Keywords


Humanoid Robot; Kalman Filter; Center of Pressure; PID Control; Load Cell

Full Text:

PDF

References


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, 2020, https://doi.org/10.12928/biste.v2i2.922.

I. Rifajar and A. Fadlil, “The Path Direction Control System for Lanange Jagad Dance Robot Using the MPU6050 Gyroscope Sensor,” International Journal of Robotics and Control Systems, vol. 1, no. 1, pp. 27–40, 2021, https://doi.org/10.31763/ijrcs.v1i1.225.

A. Nawrocka, M. Nawrocki, and A. Kot, “The use of Kalman Filter in Control the Balancing Robot,” Proceedings of the 2020 21st International Carpathian Control Conference, 2020, https://doi.org/10.1109/ICCC49264.2020.9257212.

K. Joni, M. Ulum, T. Prasetyo, and A. Y. Maulana, “Dynamic balancing humanoid robot using completmentary filter to optimized pid controller,” Journal of Physics: Conference Series, vol. 1211, no. 1, p. 012046, 2019, https://doi.org/10.1088/1742-6596/1211/1/012046.

A. H. Alasiry, N. F. Satria and A. Sugiarto, “Balance Control of Humanoid Dancing Robot ERISA while Walking on Sloped Surface using PID,” 2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), pp. 577-581, 2018, https://doi.org/10.1109/ISRITI.2018.8864447.

S. Kim, K. Hirota, T. Nozaki and T. Murakami, “Human Motion Analysis and Its Application to Walking Stabilization with COG and ZMP,” IEEE Transactions on Industrial Informatics, vol. 14, no. 11, pp. 5178-5186, 2018, https://doi.org/10.1109/TII.2018.2830341.

R. Subburaman, D. Kanoulas, L. Muratore, N. G. Tsagarakis, and J. Lee, “Human inspired fall prediction method for humanoid robots,” Robotics and Autonomous Systems, vol. 121, p. 103257, 2019, https://doi.org/10.1016/j.robot.2019.103257.

M. S. Grewal, A. P. Andrews, C. G. Bartone, “Kalman Filtering,” Global Navigation Satellite Systems, Inertial Navigation, and Integration, pp.355-417, 2020, https://doi.org/10.1002/9781119547860.ch10.

Y. Xu, K. Xu, J. Wan, Z. Xiong and Y. Li, “Research on Particle Filter Tracking Method Based on Kalman Filter,” 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), pp. 1564-1568, 2018, https://doi.org/10.1109/IMCEC.2018.8469578.

G. Revach, N. Shlezinger, X. Ni, A. L. Escoriza, R. J. G. van Sloun and Y. C. Eldar, “KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics,” IEEE Transactions on Signal Processing, vol. 70, pp. 1532-1547, 2022, https://doi.org/10.1109/TSP.2022.3158588.

A. A. Rafiq, W. N. Rohman, S. D. Riyanto, “Development of a simple and low-cost smartphone gimbal with MPU-6050 sensor,” Journal of Robotics and Control (JRC), vol. 1, no. 4, pp. 136-140, 2020, https://doi.org/10.18196/jrc.1428.

I. Rifajar, A. Fadlil, “The Path Direction Control System for Lanange Jagad Dance Robot Using the MPU6050 Gyroscope Sensor,” International Journal of Robotics and Control Systems, vol. 1, no. 1, pp. 27-40, 2021, https://doi.org/10.31763/ijrcs.v1i1.225.

H. Heriyadi, H. Fajrin, and W. Kartika, “Prayer Guide Gyroscope Bracelet for The Deaf Using MPU6050 Sensor”, Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics, vol. 4, no. 1, pp. 36-40, 2022, https://doi.org/10.35882/ijeeemi.v4i1.6.

L. Yang, H. Yao, J. Wang, C. Jiang, A. Benslimane and Y. Liu, “Multi-UAV-Enabled Load-Balance Mobile-Edge Computing for IoT Networks,” IEEE Internet of Things Journal, vol. 7, no. 8, pp. 6898-6908, 2020, https://doi.org/10.1109/JIOT.2020.2971645.

C. U. Ebuzeme, Z. A. Quadri, O. Noah, E. O. Ogedengbe, C. Eguma, “Performance Evaluation of an Aerodynamic Blade Model Using a Bottom-mounted Force Balance System,” AIAA Propulsion and Energy 2019 Forum, p. 4160, 2019, https://doi.org/10.2514/6.2019-4160.

B. A. Alqahtani, et al., “Effect of community-based group exercise interventions on Standing balance and strength in independent living older adults,” Journal of geriatric physical therapy, vol. 42, no. 4, pp. E7-E15, 2019, https://doi.org/10.1519/JPT.0000000000000221.

A. A. Neghabi, N. Jafari Navimipour, M. Hosseinzadeh and A. Rezaee, “Load Balancing Mechanisms in the Software Defined Networks: A Systematic and Comprehensive Review of the Literature,” IEEE Access, vol. 6, pp. 14159-14178, 2018, https://doi.org/10.1109/ACCESS.2018.2805842.

T. V. Chien, E. Björnson and E. G. Larsson, “Optimal Design of Energy-Efficient Cell-Free Massive Mimo: Joint Power Allocation and Load Balancing,” ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5145-5149, 2020, https://doi.org/10.1109/ICASSP40776.2020.9054083.

D. Saputra, A. Ma'arif, H. Maghfiroh, P. Chotikunnan, S. N. Rahmadhia, “Design and Application of PLC-based Speed Control for DC Motor Using PID with Identification System and MATLAB Tuner,” International Journal of Robotics and Control Systems, vol. 3, no. 2, pp. 233-244, 2023, https://doi.org/10.31763/ijrcs.v3i2.775.

H. Fang, N. Tian, Y. Wang, M. Zhou and M. A. Haile, “Nonlinear Bayesian estimation: from Kalman filtering to a broader horizon,” IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 2, pp. 401-417, 2018, https://doi.org/10.1109/JAS.2017.7510808.




DOI: https://doi.org/10.59247/csol.v1i2.22

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Cisi Fitri Wulandari, Abdul Fadlil

 

Control Systems and Optimization Letters
ISSN: 2985-6116
Website: https://ejournal.csol.or.id/index.php/csol
Email: alfian_maarif@ieee.org
Publisher: Peneliti Teknologi Teknik Indonesia
Address: Jl. Empu Sedah No. 12, Pringwulung, Condongcatur, Kec. Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta 55281, Indonesia