Simulation of Autonomous Navigation Mobile Robot System

Authors

  • Mofeed Turky Rashid Electrical Engineering Department, University of Basrah, Basrah, Iraq Author
  • Huda Ameer Zak Computer Science Department, Shatt Al-arab College University, Basrah, Iraq Author
  • Rana Jassim Mohammed Computer Science Department, Education of Pure Science College, University of Basrah, Basrah, Iraq Author

Keywords:

Autonomous mobile robot, DFS, BFS, image processing, maze

Abstract

The goal of real-time mobile robots is to travel in the shortest path between two points in a navigation environment. Autonomous navigation allows robots to planning this path without the need for human intervention. In this paper, Autonomous navigation mobile robot system has been simulated by MATLAB which a camera is used to snapshotting robot environment represented by maze while image processing techniques are used for extracting maze parameters. These parameters are used to planning the shortest path between start point and target based on Depth-first Search (DFS) and Breadth-first Search (BFS) searching algorithms.

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Published

2014-07-01

Issue

Vol. 18 No. 4 (2014): Journal of Engineering and Development

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The Journal of Engineering and Sustainable Development is an open-access journal that all contents are free of charge. Articles of this journal are licensed under the terms of the Creative Commons Attribution International Public License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) that licensees are unrestrictly allowed to search, download, share, distribute, print, or link to the full texts of the articles, crawl them for indexing and reproduce any medium of the articles provided that they give the author(s) proper credits (citation). The journal allows the author(s) to retain the copyright of their published article.
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How to Cite

Simulation of Autonomous Navigation Mobile Robot System. (2014). Journal of Engineering and Sustainable Development, 18(4), 25-38. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/829