Implementasi Teknologi Motion Capture untuk Pengendalian Robot Lengan Menggunakan Sensor MPU-6050 dan Flex Sensor

Andri Suhartono

Abstract


This research aims to evaluate the capability of motion capture technology in capturing the movement of the left human arm and applying it to an arm robot. In this research, three MPU-6050 sensors are used, which are a combination of 3D accelerometer and 3D gyroscope to obtain the position and orientation of the left human arm, as well as one flex sensor to obtain finger bend or hand grip data. In this research, the optimal processing and data transmission delay time is 75 ms. Test results show an average accuracy rate of 87% in controlling the robot for 30 seconds. Results obtained from the used sensors are stable when in motion, but there is a slight stability problem when in a stationary position. Overall, this research concludes that motion capture technology can be used to assist humans in controlling robot movement with precision and ease.


Keywords


Interaksi manusia-robot; Motion capture; Robot lengan; Sensor; Tracking gerak lengan

Full Text:

PDF

References


J. L. e. al., "Real-Time Human Motion Capture Based on Wearable Inertial Sensor Networks," IEEE Internet of Things Journal, vol. 9, pp. 8953-8966, 2022.

L. Tong, R. Liu and L. Peng, "LSTM-Based Lower Limbs Motion Reconstruction Using Low-Dimensional Input of Inertial Motion Capture System," IEEE Sensors Journal, vol. 20, pp. 3667-3677, 2020.

W. X. e. al, "Human-robot Interaction Oriented Human-in-the-loop Real-time Motion Imitation on a Humanoid Tri-Co Robot," in 3rd International Conference on Advanced Robotics and Mechatronics (ICARM), Singapore, 2018.

D. Go, H. Hyung, D. Lee and H. U. Yoon, "Andorid Robot Motion Generation Based on Video-Recorded Human Demonstrations," in IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Nanjing, China, 2018.

Y. Wei, "A Comprehensive Approach to the Generation of Human-Like Arm Movements on Robot NAO," IEEE Access, vol. 8, pp. 172869-172881, 2020.




DOI: https://doi.org/10.31284/p.snestik.2023.3994

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Andri Suhartono

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.