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Fusion: Practice and Applications
Volume 15 , Issue 2, PP: 89-101 , 2024 | Cite this article as | XML | Html |PDF

Title

Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments

  Mohammed R. Hashim Al-Dahhan 1 * ,   Mahmood Abdulrazzaq Alsaadi 2 ,   Ruqayah R. Al-Dahhan 3 ,   Salah A. Aliesawi 4

1  College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq
    (mohammed.rabeea@uoanbar.edu.iq)

2  Computer Science Department, Al-Maarif University Collage, Ramadi, Anbar, Iraq
    (alsaadi.m@uoa.edu.iq)

3  College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq
    (ruqayah85@uoanbar.edu.iq)

4  College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq
    (salah_eng1996@uoanbar.edu.iq)

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Doi   :   https://doi.org/10.54216/FPA.150208

Received: August 24, 2023 Revised: December 24, 2023 Accepted: March 27, 2024

Abstract :

Intelligent mobile robots move on uncertain grounds, thus requiring good navigation strategies for things like path tracking and obstacle avoidance. This research uses an Omni-drive mobile robot to autonomously approach given objectives in different situations encountered in static and dynamic environments. The paper compares two distinct controllers – fuzzy logic controller and neural network controller- that lead the mobile robot towards its destination without hitting obstacles. These are responsible for adjusting the linear and angular velocities of a mobile robot which makes adaptive navigation possible during real-time. The experimental results have depicted the adaptability of each controller as well as its efficiency especially when dealing with uncertainties involved with the mobile robot navigation system. By systematically evaluating and contrasting them, this study brings out the best performance between Fuzzy Logic and Neural Network Controllers regarding enhancing the autonomy and robustness of Mobile Robots. This research helps to advance knowledge in autonomous systems for practical applications, which will give rise to more efficient navigational techniques for mobile robots; thus, efficient systems that are autonomous become more reliable today. The results show that these controllers are effective in safely steering the robot from its starting point to a specified destination without hitting obstacles.

Keywords :

Omni-drive robot; collision environment; neural network controller; type2 fuzzy logic controller.

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Cite this Article as :
Style #
MLA Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. "Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments." Fusion: Practice and Applications, Vol. 15, No. 2, 2024 ,PP. 89-101 (Doi   :  https://doi.org/10.54216/FPA.150208)
APA Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. (2024). Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments. Journal of Fusion: Practice and Applications, 15 ( 2 ), 89-101 (Doi   :  https://doi.org/10.54216/FPA.150208)
Chicago Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. "Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments." Journal of Fusion: Practice and Applications, 15 no. 2 (2024): 89-101 (Doi   :  https://doi.org/10.54216/FPA.150208)
Harvard Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. (2024). Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments. Journal of Fusion: Practice and Applications, 15 ( 2 ), 89-101 (Doi   :  https://doi.org/10.54216/FPA.150208)
Vancouver Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments. Journal of Fusion: Practice and Applications, (2024); 15 ( 2 ): 89-101 (Doi   :  https://doi.org/10.54216/FPA.150208)
IEEE Mohammed R. Hashim Al-Dahhan, Mahmood Abdulrazzaq Alsaadi, Ruqayah R. Al-Dahhan, Salah A. Aliesawi, Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments, Journal of Fusion: Practice and Applications, Vol. 15 , No. 2 , (2024) : 89-101 (Doi   :  https://doi.org/10.54216/FPA.150208)
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