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Mobile Robot Navigation and Obstacle-avoidance using ANFIS in Unknown Environment

by Mohammed Algabri, Hassan Mathkour, Hedjar Ramdane
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 14
Year of Publication: 2014
Authors: Mohammed Algabri, Hassan Mathkour, Hedjar Ramdane
10.5120/15952-5400

Mohammed Algabri, Hassan Mathkour, Hedjar Ramdane . Mobile Robot Navigation and Obstacle-avoidance using ANFIS in Unknown Environment. International Journal of Computer Applications. 91, 14 ( April 2014), 36-41. DOI=10.5120/15952-5400

@article{ 10.5120/15952-5400,
author = { Mohammed Algabri, Hassan Mathkour, Hedjar Ramdane },
title = { Mobile Robot Navigation and Obstacle-avoidance using ANFIS in Unknown Environment },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 14 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number14/15952-5400/ },
doi = { 10.5120/15952-5400 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:12:46.140433+05:30
%A Mohammed Algabri
%A Hassan Mathkour
%A Hedjar Ramdane
%T Mobile Robot Navigation and Obstacle-avoidance using ANFIS in Unknown Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 14
%P 36-41
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Navigation and obstacle avoidance in an unknown environment is proposed in this paper using hybrid neural network with fuzzy logic controller. The overall system is termed as Adaptive Neuro Fuzzy Inference System (ANFIS). ANFIS combines the benefits of fuzzy logic and neural networks for the purpose of achieving robotic navigation task. Simulation results are presented using Khepera Simulator (KiKs) within MATLAB environment. Moreover, experimental results are obtained using Khepera III platform.

References
  1. Obe, O. and Dumitrache, I. 2012. "Adaptive Neuro-Fuzzy Controler With Genetic Training For Mobile Robot Control," International Journal of Computers Communications & Control, vol. 7, no. 1, pp. 135–146.
  2. AbuBaker, A. 2012. "A Novel Mobile Robot Navigation System Using Neuro-Fuzzy Rule-Based Optimization Technique," Research Journal of Applied Sciences, vol. 4.
  3. Chen, C. and Richardson, P. 2012. "Mobile robot obstacle avoidance using short memory: a dynamic recurrent neuro-fuzzy approach," Transactions of the Institute of Measurement and Control, vol. 34, no. 2–3, pp. 148–164.
  4. Kundu, S. , Parhi, R. , Deepak ,B. B. V. L. 2012. "Fuzzy-Neuro based Navigational Strategy for Mobile Robot," International Journal of Scientific & Engineering Research, Volume 3, Issue 6.
  5. Zhu, A. and Yang, S. X. 2007. "Neurofuzzy-based approach to mobile robot navigation in unknown environments," Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 37, no. 4, pp. 610–621.
  6. Jang, J. S. R. 1993. ANFIS: Adaptive-network-based fuzzy inference systems. ,IEEE Trans. on Syst. Man, and Cybern. , vol. 23 no. 5, pp. 665-685.
  7. KiKS is a Khepera Simulator. http://www. theodorstorm. se/index/2866. html (02, June, 2013, date accessed).
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy logic controller neural network ANFIS mobile robot navigation Khepera III.

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