Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Inverse Kinematics Solution of a Robot Arm based on Adaptive Neuro Fuzzy Interface System

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2019
Authors:
Gjorgji Vladimirov, Saso Koceski
10.5120/ijca2019919268

Gjorgji Vladimirov and Saso Koceski. Inverse Kinematics Solution of a Robot Arm based on Adaptive Neuro Fuzzy Interface System. International Journal of Computer Applications 178(39):10-14, August 2019. BibTeX

@article{10.5120/ijca2019919268,
	author = {Gjorgji Vladimirov and Saso Koceski},
	title = {Inverse Kinematics Solution of a Robot Arm based on Adaptive Neuro Fuzzy Interface System},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2019},
	volume = {178},
	number = {39},
	month = {Aug},
	year = {2019},
	issn = {0975-8887},
	pages = {10-14},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume178/number39/30791-2019919268},
	doi = {10.5120/ijca2019919268},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Nowadays, robot arms are used as standalone or intrinsic part of many robot systems in various fields and applications. The design and structure of robot arms varies depending on multiple constraints such as the tasks they have to perform, working environment in which they have to operate, the dimensions of the objects they have to peak, etc. Every robot arm, regardless of its design and structure, is aimed to perform some movement that has to be carefully analyzed and planned. During this process, usually two types of motion are analyzed. The first one aims at finding the position of the end effector when the angles between the robot arm links are known. This problem is usually denoted as direct kinematics. The second one, known as inverse kinematics, aims at solving the opposite problem i.e. to determine the angles between links when the position of the end effector is known. This paper presents an inverse kinematics solution of two degrees of freedom planar robot arm based on Adaptive Neuro Fuzzy Interface System (ANFIS). The proposed model is experimentally evaluated and the obtained results are discussed.

References

  1. Loshkovska, Suzana, and Saso Koceski, eds. ICT innovations 2015: Emerging technologies for better living. Vol. 399. Springer, 2015.
  2. Koceski, Saso, and Biljana Petrevska. "Empirical evidence of contribution to e-tourism by application of personalized tourism recommendation system." Annals of the Alexandru Ioan Cuza University-Economics 59, no. 1 (2012): 363-374.
  3. Trajkovik, Vladimir, Elena Vlahu-Gjorgievska, Saso Koceski, and Igor Kulev. "General assisted living system architecture model." In International Conference on Mobile Networks and Management, pp. 329-343. Springer, Cham, 2014.
  4. Stojanov, Done, and Saso Koceski. "Topological MRI prostate segmentation method." In Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on, pp. 219-225. IEEE, 2014
  5. Koceski, Saso, and Natasa Koceska. "Evaluation of an assistive telepresence robot for elderly healthcare." Journal of medical systems 40, no. 5 (2016): 121.
  6. Stojanov, Done, Aleksandra Mileva, and Sašo Koceski. "A new, space-efficient local pairwise alignment methodology." Advanced Studies in Biology 4, no. 2 (2012): 85-93.
  7. Koceski, Saso, and Natasa Koceska. "Challenges of videoconferencing distance education-a student perspective." International Journal of Information, Business and Management 5, no. 2 (2013): 274.
  8. Koceski, Saso, Natasa Koceska, and Ivica Kocev. "Design and evaluation of cell phone pointing interface for robot control." International Journal of Advanced Robotic Systems 9, no. 4 (2012): 135.
  9. Koceski, Saso, Stojanche Panov, Natasa Koceska, Pierluigi Beomonte Zobel, and Francesco Durante. "A novel quad harmony search algorithm for grid-based path finding." International Journal of Advanced Robotic Systems 11, no. 9 (2014): 144.
  10. Koceska, Natasa, Saso Koceski, Francesco Durante, Pierluigi Beomonte Zobel, and Terenziano Raparelli. "Control architecture of a 10 DOF lower limbs exoskeleton for gait rehabilitation." International Journal of Advanced Robotic Systems 10, no. 1 (2013): 68.
  11. Serafimov, Kire, Dimitrija Angelkov, Natasa Koceska, and Saso Koceski. "Using mobile-phone accelerometer for gestural control of soccer robots." In Embedded Computing (MECO), 2012 Mediterranean Conference on, Bar, Montenegro, pp. 140-143. 2012.
  12. Koceska, Natasa, and Saso Koceski. "Financial-Economic Time Series Modeling and Prediction Techniques–Review." Journal of Applied Economics and Business 2, no. 4 (2014): 28-33.
  13. Kucuk, Serdar, and Zafer Bingul. "Robot kinematics: Forward and inverse kinematics." In Industrial Robotics: Theory, Modelling and Control. IntechOpen, 2006.
  14. Pérez-Rodríguez, Rodrigo, Alexis Marcano-Cedeño, Úrsula Costa, Javier Solana, César Cáceres, Eloy Opisso, Josep M. Tormos, Josep Medina, and Enrique J. Gómez. "Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation." Expert Systems with Applications 39, no. 10 (2012): 9612-9622.
  15. J. J. Craig, Introduction to Robotics: Mechanisms and Controls, Addison-Wesley, Reading, MA, 1989.
  16. G. C. S. Lee, Robot Arm Kinematics, Dynamics and Control, Computer, Vol. 15, Issue. 12, pp. 62-79, 1982.
  17. J. U. Korein, N. I. Balder, Techniques for generating the goal-directed motion of articulated structures, IEEE Computer Graphics and Applications, Vol. 2, Issue. 9, pp. 71-81, 1982.
  18. KöKer, RaşIt. "A genetic algorithm approach to a neural-network-based inverse kinematics solution of robotic manipulators based on error minimization." Information Sciences 222 (2013): 528-543.
  19. Momani, Shaher, Zaer S. Abo-Hammour, and Othman MK Alsmadi. "Solution of inverse kinematics problem using genetic algorithms." Applied Mathematics & Information Sciences 10, no. 1 (2016): 225.
  20. Ram, R. V., P. M. Pathak, and S. J. Junco. "Inverse kinematics of mobile manipulator using bidirectional particle swarm optimization by manipulator decoupling." Mechanism and Machine Theory 131 (2019): 385-405.
  21. Dereli, Serkan, and Raşit Köker. "Calculation of the inverse kinematics solution of the 7-DOF redundant robot manipulator by the firefly algorithm and statistical analysis of the results in terms of speed and accuracy." Inverse Problems in Science and Engineering (2019): 1-13.
  22. Almusawi, Ahmed RJ, L. Canan Dülger, and Sadettin Kapucu. "A new artificial neural network approach in solving inverse kinematics of robotic arm (denso vp6242)." Computational intelligence and neuroscience 2016 (2016).
  23. Hošovský, A., J. Piteľ, K. Židek, M. Tóthová, J. Sárosi, and L. Cveticanin. "Dynamic characterization and simulation of two-link soft robot arm with pneumatic muscles." Mechanism and Machine Theory 103 (2016): 98-116.
  24. Raheem, Firas A., Hind Z. Khaleel, and Mostafa K. Kashan. "Robot Arm Design for Children Writing Ability Enhancement using Cartesian Equations based on ANFIS." In 2018 Third Scientific Conference of Electrical Engineering (SCEE), pp. 150-155. IEEE, 2019.

Keywords

Robot arm, ANFIS, Robot arm with two joint, Robot arm with two links, inverse kinematics, inverse kinematic on 2 joint robot.