CFP last date
22 April 2024
Reseach Article

Navigation Control of Autonomous Robot using Fuzzy Logic

Published on August 2017 by Amar A. Yelane, S. R. Vaidya, Sandip B. Pawar
International Conference on Quality Up-gradation in Engineering Science and Technology
Foundation of Computer Science USA
ICQUEST2016 - Number 1
August 2017
Authors: Amar A. Yelane, S. R. Vaidya, Sandip B. Pawar
a6d847be-3ff9-48d3-ae0d-76f70e47b809

Amar A. Yelane, S. R. Vaidya, Sandip B. Pawar . Navigation Control of Autonomous Robot using Fuzzy Logic. International Conference on Quality Up-gradation in Engineering Science and Technology. ICQUEST2016, 1 (August 2017), 1-4.

@article{
author = { Amar A. Yelane, S. R. Vaidya, Sandip B. Pawar },
title = { Navigation Control of Autonomous Robot using Fuzzy Logic },
journal = { International Conference on Quality Up-gradation in Engineering Science and Technology },
issue_date = { August 2017 },
volume = { ICQUEST2016 },
number = { 1 },
month = { August },
year = { 2017 },
issn = 0975-8887,
pages = { 1-4 },
numpages = 4,
url = { /proceedings/icquest2016/number1/28125-1602/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Quality Up-gradation in Engineering Science and Technology
%A Amar A. Yelane
%A S. R. Vaidya
%A Sandip B. Pawar
%T Navigation Control of Autonomous Robot using Fuzzy Logic
%J International Conference on Quality Up-gradation in Engineering Science and Technology
%@ 0975-8887
%V ICQUEST2016
%N 1
%P 1-4
%D 2017
%I International Journal of Computer Applications
Abstract

In the field of electronic engineering the work of automation is growing at speed of light. The fundamental concept of autonomous operation depends on technique and logic that we are using. The simple fundamental concept of operating autonomous robot or simply we can say that a mobile robot is a navigation of that robot. The navigation consists of providing the specific path to follow optimal distance. In case if any obstacles are hitting to that robot, the robot should understand how to find a path by avoiding that obstacles. Simple thing is that we can direct that robot with some logic. That simple logic is explained in this paper. The way of navigation is decided by that robot itself by using fuzzy logic. It will direct that robot how to avoid any obstacles which is having various characteristics depends on nature i. e. obstacles is moving or static, height of that obstacles etc. The fuzzy logic criterion gives brief explanation about this concept.

References
  1. Md. Arafat Hossain, Israt Ferdous, "Autonomous Robot Path Planning in Dynamic Environment Using a New Optimization Technique Inspired by Bacterial Foraging Technique", International Conference on Electrical Information and Communication Technology (EICT) , 2013.
  2. Mostafa Nazari , Javad Amiryan , Eslam Nazemi ," Improvement of Robot Navigation Using Fuzzy Method", IEEE, 2013.
  3. Cheng-Hsiung Chinag, Chiehyi Ding, "Robot Navigation in Dynamic Environments using Fuzzy Logic and Trajectory Prediction Table", 2014 International Conference on Fuzzy Theory and Its Applications (iFUZZY2014) November 26-28, 2014.
  4. Qiang Liu and Jiachen Ma, Qi Zhang, "PSO-based Parameters Optimization of Multi-Robot Formation Navigation in Unknown Enviroment," Proceedings of 10th World congress on intelligent control and automation July 6-8, 2012.
  5. Bremermann, H. J. "Chemotaxis and optimization", Journal of Franklin Institute 297, pp. 397-404, 2004.
  6. Dhariwal, A. ; Sukhatme, G. S. ; Requicha, A. A. G. ''Bacterium-inspired robots for environmental monitoring'', Proceedings of the IEEE International Conference on Robotics & Automation, New Orleans, LA, pp. 1496-1443, 2004.
  7. Zaidi, Ines, et al. "Positive observation of Takagi-Sugeno systems," Methods and Models in Automation and Robotics (MMAR), 2012 17th International Conference on. IEEE, 2012.
  8. G. Kokila, Mr. M. Karnan, Mr. R. Sivakumar, "Immigrants and Memory Schemes For Dynamic Shortest Path Routing Problems In Mobile Adhoc Networks Using PSO, BFO", International Journal of Computer Science and Management Research, Vol 2, Issue 5, 2013.
  9. Anupama sharma, Miss Sampada Satav "Path Navigation Using Computational Intelligence", International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 7, 2012.
  10. Zaidi, Ines, et al. "Positive observation of Takagi-Sugeno systems," Methods and Models in Automation and Robotics (MMAR), 2012 17th International Conference on. IEEE, 2012.
  11. Most, Thomas. "Variance-based sensitivity analysis in the presence of correlated input variables. " Proc. 5th Int. Conf. Reliable Engineering Computing (REC), Brno, Czech Republic. 2012.
  12. M. Phillips and M. Likhachev, "Sipp: Safe interval path planning for dynamic environments," in Proceedings of 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 5628-5635, 2011.
  13. M. Faisal, K. Al-Mutib, R. Hedjar, H. Mathkour, M. Alsulaiman, and E. Mattar, "Multi modules fuzzy logic for mobile robots navigation and obstacle avoidance in unknown indoor dynamic environment," in Proceedings of 2013 International Conference on Systems, Control and Informatics, pp. 371-379, 2013.
  14. Zhiqiang Cao, Min Tan, Shuo Wang, et al. The optimization research of formation control for multiple mobile robots. Proceeding of the 4th World Congress on Intelligent Control and Automation, 2002, 1270~1274.
  15. S. Berman, Y. Edan, and M. Hamshidi, "Navigation of decentralized autonomous automatic guided vehicles in material handling," IEEE Trans. on Robot. Automat. , vol. 19, no. 4, pp. 743-749, 2004.
Index Terms

Computer Science
Information Sciences

Keywords

Autonomous Robot Mobile Robot Fuzzy Logic Navigation