Sistem Pengaturan Orientasi Arah Hadap Robot Humanoid Menggunakan Inertial Measuring Unit dan Time of Flight

Dimas Adi Prayoga; Totok Winarno; Indrazno Siradjuddin

doi:10.33795/elkolind.v12i1.3292

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Abstract

Robot humanoid pada saat berjalan memiliki orientasi arah hadap yang tidak sesuai sehingga menghasilkan nilai error arah orientasi arah hadap diatas 20 derajat. Perlu adanya kontrol sistem yang dapat meningkatkan akurasi arah hadap robot humanoid dengan menggunakan Inertial Measuring Unit dan Time of Flight. Inertial Measuring Unit terintegrasi dengan imu odometry yang memanfaatkan sistem pengukuran seperti giroskop dan akselerometer digunakan untuk memproyeksikan posisi relatif, kecepatan, dan akselerasi dari gerakan aktuator. Time of Flightmerupakan metode yang digunakan untuk mengukur jarak robot dengan obyek untuk menghindari gangguan yang dapat membuat error orientasi arah hadap. Penelitian yang dilakukan bertujuan agar robot humanoid dapat berjalan sesuai dengan arah hadap yang ditentukan. Kedua masukan dalam sistem ini akan dilakukan proses kombinasi dan filterisasi dengan metode extended kalman filter kemudian dijadikan masukan pada proses error kontrol PID. Hasil keluaran kontroler PID adalah angle move yaw pada parameter jalan robot humanoid yang memiliki nilai error orientasi arah hadap dibawah 4% dari nilai orientasi arah hadap yang telah direncanakan.

Keywords

Robot Humanoid Orientasi Arah Hadap Inertial Measuring Unit Time of Flight

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

References

I. Siradjuddin, L. Behera, T. M. Mcginnity, and S. Coleman, “A position based visual tracking system for a 7 DOF robot manipulator using a Kinect camera.”
P. H. Setiawan, “Analisis Inverse Kinematics Tersegmentasi Berbasis Geometris Pada Robot Humanoid Saat Walking Gait System for Humanoid Robot,” p. 28, 2016.
M. N. A. Roni, “Pengembangan Arah Hadap Robot Dan Lintasan Perencanaan Untuk Krakatau Msl,” Jecsit, vol. 1, no. 1, pp. 42–50, 2021.
G. Vasilyev, A. Sagitov, L. Gavrilova, K. L. Su, and T. Tsoy, “Walking algorithm for robotis OP3 humanoid robot with force sensors,” Proceedings - International Conference on Developments in eSystems Engineering, DeSE, vol. October-20, pp. 20–23, 2019, doi: 10.1109/DeSE.2019.00014.
F. D. R. Rizaldy, I. Siradjuddin, and T. Winarno, “Sistem Lokalisasi Robot Humanoid Menggunakan Monocular Camera dan IMU,” Vol 9, No 2 (2022): Elkolind Vol. 9 No. 2 (Juli 2022), vol. 9, 2022.
J. M. Ibarra Zannatha and R. Cisneros Limón, “Forward and inverse kinematics for a small-sized humanoid robot,” in CONIELECOMP 2009 - 19th International Conference on Electronics Communications and Computers, 2009, pp. 111–118. doi: 10.1109/CONIELECOMP.2009.50.
S. N. Aslan, R. Ozalp, A. Uear, and C. Guzelis, “End-To-End Learning from Demonstation for Object Manipulation of Robotis-Op3 Humanoid Robot,” INISTA 2020 - 2020 International Conference on INnovations in Intelligent SysTems and Applications, Proceedings, 2020, doi: 10.1109/INISTA49547.2020.9194630.
Z. Li, Z. Su, and T. Yang, “Design of intelligent mobile robot positioning algorithm based on iμodometer/lidar,” in Proceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019, Institute of Electrical and Electronics Engineers Inc., Aug. 2019, pp. 627–631. doi: 10.1109/SDPC.2019.00118.
U. B. Himmelsbach, T. M. Wendt, N. Hangst, and P. Gawron, “Single Pixel Time-of-Flight Sensors for Object Detection and Self-Detection in Three-Sectional Single-Arm Robot Manipulators,” in Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019, Institute of Electrical and Electronics Engineers Inc., Mar. 2019, pp. 250–253. doi: 10.1109/IRC.2019.00046.
M. B. Alatise and G. P. Hancke, “Pose estimation of a mobile robot based on fusion of IMU data and vision data using an extended kalman filter,” Sensors (Switzerland), vol. 17, no. 10, Oct. 2017, doi: 10.3390/s17102164.
L. Jetto, S. Longhi, and G. Venturini, “Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots,” IEEE Transactions on Robotics and Automation, vol. 15, no. 2, pp. 219–229, 1999, doi: 10.1109/70.760343.
J. C. Basilio and S. R. Matos, “Design of PI and PID controllers with transient performance specification,” IEEE Transactions on Education, vol. 45, no. 4, pp. 364–370, 2002, doi: 10.1109/TE.2002.804399.

References

I. Siradjuddin, L. Behera, T. M. Mcginnity, and S. Coleman, “A position based visual tracking system for a 7 DOF robot manipulator using a Kinect camera.”

P. H. Setiawan, “Analisis Inverse Kinematics Tersegmentasi Berbasis Geometris Pada Robot Humanoid Saat Walking Gait System for Humanoid Robot,” p. 28, 2016.

M. N. A. Roni, “Pengembangan Arah Hadap Robot Dan Lintasan Perencanaan Untuk Krakatau Msl,” Jecsit, vol. 1, no. 1, pp. 42–50, 2021.

G. Vasilyev, A. Sagitov, L. Gavrilova, K. L. Su, and T. Tsoy, “Walking algorithm for robotis OP3 humanoid robot with force sensors,” Proceedings - International Conference on Developments in eSystems Engineering, DeSE, vol. October-20, pp. 20–23, 2019, doi: 10.1109/DeSE.2019.00014.

F. D. R. Rizaldy, I. Siradjuddin, and T. Winarno, “Sistem Lokalisasi Robot Humanoid Menggunakan Monocular Camera dan IMU,” Vol 9, No 2 (2022): Elkolind Vol. 9 No. 2 (Juli 2022), vol. 9, 2022.

J. M. Ibarra Zannatha and R. Cisneros Limón, “Forward and inverse kinematics for a small-sized humanoid robot,” in CONIELECOMP 2009 - 19th International Conference on Electronics Communications and Computers, 2009, pp. 111–118. doi: 10.1109/CONIELECOMP.2009.50.

S. N. Aslan, R. Ozalp, A. Uear, and C. Guzelis, “End-To-End Learning from Demonstation for Object Manipulation of Robotis-Op3 Humanoid Robot,” INISTA 2020 - 2020 International Conference on INnovations in Intelligent SysTems and Applications, Proceedings, 2020, doi: 10.1109/INISTA49547.2020.9194630.

Z. Li, Z. Su, and T. Yang, “Design of intelligent mobile robot positioning algorithm based on iμodometer/lidar,” in Proceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019, Institute of Electrical and Electronics Engineers Inc., Aug. 2019, pp. 627–631. doi: 10.1109/SDPC.2019.00118.

U. B. Himmelsbach, T. M. Wendt, N. Hangst, and P. Gawron, “Single Pixel Time-of-Flight Sensors for Object Detection and Self-Detection in Three-Sectional Single-Arm Robot Manipulators,” in Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019, Institute of Electrical and Electronics Engineers Inc., Mar. 2019, pp. 250–253. doi: 10.1109/IRC.2019.00046.

M. B. Alatise and G. P. Hancke, “Pose estimation of a mobile robot based on fusion of IMU data and vision data using an extended kalman filter,” Sensors (Switzerland), vol. 17, no. 10, Oct. 2017, doi: 10.3390/s17102164.

L. Jetto, S. Longhi, and G. Venturini, “Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots,” IEEE Transactions on Robotics and Automation, vol. 15, no. 2, pp. 219–229, 1999, doi: 10.1109/70.760343.

J. C. Basilio and S. R. Matos, “Design of PI and PID controllers with transient performance specification,” IEEE Transactions on Education, vol. 45, no. 4, pp. 364–370, 2002, doi: 10.1109/TE.2002.804399.

Sistem Pengaturan Orientasi Arah Hadap Robot Humanoid Menggunakan Inertial Measuring Unit dan Time of Flight

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