Email this article Analisa Inverse Kinematics Pada Prototype 3-DoF Arm Robot Dengan Metode Anfis
Abstract
Perkembangan teknologi yang sudah semakin maju memberi dampak pada perkembangan sistem kendali lengan robot. Sistem kendali lengan robot yang digunakan bermacam-macam. Beberapa teknik yang umum digunakan adalah metode forward kinematics dan inverse kinematics. Namun, metode inverse kinematics memiliki kompleksitas yang tinggi karena diperlukan perhitungan fungsi turunan dari forward kinematics. Metode terbaru yang saat ini dapat digunakan yaitu metode Adaptive Neuro Fuzzy Inference System (ANFIS). Pada umumnya ANFIS dilakukan untuk memprediksi data keluaran berdasarkan pelatihan hubungan data masukan dan data keluaran yang dimuat dalam dataset. Penerapan metode ANFIS yang dilakukan pada penelitian ini sebagai solusi inverse kinematics untuk mengurangi kompleksitas dari metode tersebut. Berdasarkan hasil pengujian yang dilakukan bahwa RMSE pada inverse kinematics bernilai 25.36137736 sedangkan RMSE pada metode ANFIS bernilai 42.18690271. Meskipun nilai error yang dihasilkan dari metode ANFIS cukup besar akibat beberapa faktor error yang mempengaruhinya, metode ANFIS ini terbukti dapat digunakan untuk kontrol lengan robot 3-DOF.
Keywords
Full Text:
PDFReferences
T. Bräunl, “Embedded Robotics: Mobile Robot Design and Application with Embedded Systems,” Springer, 2006
J. J. Craig, “Introduction to Robotics Mechanics and Control,” Pearson Education International, 2005.
T. Dewi, C. Anggraini, P. Risma, Y. Oktarina, and M. Muslikhin, “Motion Control Analysis Of Two Collaborative Arm Robots In Fruit Packaging System,” SINERGI, vol. 25, no. 2, p. 217, Feb. 2021, doi: 10.22441/sinergi.2021.2.013.
L. Qingsheng and J. Andika, “Analysis Of Kinematic For Legs Of A Hexapod Using Denavit-Hartenberg Convention,” SINERGI, vol. 22, no. 2, p. 69, Jun. 2018, doi: 10.22441/sinergi.2018.2.001.
J. Andika and K. S. Salamah, “Analisis Kinematik Pada Robot Hexapod,” Jurnal Teknologi Elektro, vol. 9, no. 2, May 2018, doi: 10.22441/jte.v9i2.4072
Z. Iklima, M. I. Muthahhar, A. Khan, and A. Zody, “Self-Learning Of Delta Robot Using Inverse Kinematics and Artificial Neural Networks,” SINERGI, vol. 25, no. 3, pp. 237–244, Jul. 2021, doi: 10.22441/sinergi.2021.3.001.
M. Crenganis, R. Breaz, G. Racz and O. Bologa, “Adaptive neuro-fuzzy inference system for kinematics solutions of redundant robots,” 2016 6th International Conference on Computers Communications and Control (ICCCC), 2016, pp. 271-276, doi: 10.1109/ICCCC.2016.7496773..
J. Demby’s, Y. Gao and G. N. DeSouza, “A Study on Solving the Inverse Kinematics of Serial Robots using Artificial Neural Network and Fuzzy Neural Network,” 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2019, pp. 1-6, doi: 10.1109/FUZZ-IEEE.2019.8858872..
M. Gaafar, A. Maged, M. Magdy, N. A. Mansour and A. El-Betar, “Design and Analysis of Experiments in ANFIS Modeling of a 3-DOF Planner Manipulator,” 2018 International Japan-Africa Conference on Electronics, Communications and Computations (JAC-ECC), 2018, pp. 169-172, doi: 10.1109/JEC-ECC.2018.8679552..
J. . -S. R. Jang, “ANFIS: adaptive-network-based fuzzy inference system,” in IEEE Transactions on Systems, Man, and Cybernetics, vol. 23, no. 3, pp. 665-685, May-June 1993, doi: 10.1109/21.256541..
I. Q. Kalimullah, A. Desikan and V. Kalaichelvi, “Analysis of a proposed algorithm for point to point control of a 3 DOF robot manipulator,” 2017 3rd International Conference on Control, Automation and Robotics (ICCAR), 2017, pp. 289-292, doi: 10.1109/ICCAR.2017.7942705..
S. H. Prabantara and A. Harjoko, “Analisis Kinematika Balik pada Kendali Robot Lengan Dental Light Berbasis Pengolahan Citra Digital Berdasarkan Isyarat Tangan,” IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), vol. 3, no. 2, pp. 207–218, 2013, doi: 10.22146/ijeis.3895.
P. Srisuk, A. Sento and Y. Kitjaidure, “Forward kinematic-like neural network for solving the 3D reaching inverse kinematics problems,” 2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2017, pp. 214-217, doi: 10.1109/ECTICon.2017.8096211.
DOI: http://dx.doi.org/10.22441/jte.2022.v13i1.003
Refbacks
- There are currently no refbacks.
Copyright (c) 2022 Jurnal Teknologi Elektro
Publisher Address:
Teknik Elektro, Fakultas Teknik, Universitas Mercu Buana
Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650
Tlp./Fax: +62215871335
Email: [email protected]
Website of Electrical Engineering
http://teknikelektro.ft.mercubuana.ac.id
p-ISSN : 2086-9479
e-ISSN : 2621-8534
Jurnal URL : http://publikasi.mercubuana.ac.id/index.php/jte
Jurnal DOI: 10.22441/jte
Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional.
The Journal is indexed by:
