Design and Synthesis of Mobile Robot Controller using Fuzzy

This paper describes a Fuzzy Logic Controller (FLC) algorithm for designing an autonomous mobile robot controller (MRC). The controller enables the robot to navigate in an unstructured environment and that avoid any encountered obstacles without human intervention. The autonomous mobile robot is fou...

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Main Authors: Islam, Md. Shabiul, Azim, Md. Anwarul, Jahan, Md. Saukat, Othman, Masuri
Format: Book Section
Language:English
Published: IEEE 2006
Subjects:
Online Access:http://shdl.mmu.edu.my/2133/
http://shdl.mmu.edu.my/2133/1/Design%20and%20Synthesis%20of%20Mobile%20Robot%20Controller%20using%20Fuzzy.pdf
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author Islam, Md. Shabiul
Azim, Md. Anwarul
Jahan, Md. Saukat
Othman, Masuri
author_facet Islam, Md. Shabiul
Azim, Md. Anwarul
Jahan, Md. Saukat
Othman, Masuri
author_sort Islam, Md. Shabiul
building MMU Institutional Repository
collection Online Access
description This paper describes a Fuzzy Logic Controller (FLC) algorithm for designing an autonomous mobile robot controller (MRC). The controller enables the robot to navigate in an unstructured environment and that avoid any encountered obstacles without human intervention. The autonomous mobile robot is found to be able to react to the environment appropriately during its navigation to avoid crashing with obstacles by turning to the proper angle while moving. The Fuzzy Logic algorithm has proven a commendable solution in dealing with certain control problems when the situation is ambiguous. One of the main difficulties faced by conventional control systems is the inability to operate in a condition with incomplete and imprecise information. As the complexity of a situation increases, a traditional mathematical model will be difficult if not impossible to implement. Fuzzy Logic is a tool for modeling uncertain systems by facilitating common sense reasoning in decision-making in the absence of complete and precise information. In this paper, the controller of an autonomous mobile robot is designed based on the theories of Fuzzy Logic. The wheeled robot is able to navigate by itself in a completely unstructured environment. The codes of MRC has written for implementing the separate modules of the Fuzzifier, Fuzzy Rule Base, Inference mechanism and Defuzzifier as hardware blocks. A behavioral model of MRC algorithm is first developed in MATLAB session with numerous data to evaluate its algorithm functionality. The development of MATLAB codes has converted into VHDL codes; for hardware implementation. Comparison results between MATLAB and VHDL of MRC algorithm also presented. Then the VHDL codes are synthesized using synthesis tool, known as Quartus II. Finally the MRC hardware blocks for VLSI design have been carried out.
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spelling mmu-21332017-01-16T09:34:30Z http://shdl.mmu.edu.my/2133/ Design and Synthesis of Mobile Robot Controller using Fuzzy Islam, Md. Shabiul Azim, Md. Anwarul Jahan, Md. Saukat Othman, Masuri QA Mathematics This paper describes a Fuzzy Logic Controller (FLC) algorithm for designing an autonomous mobile robot controller (MRC). The controller enables the robot to navigate in an unstructured environment and that avoid any encountered obstacles without human intervention. The autonomous mobile robot is found to be able to react to the environment appropriately during its navigation to avoid crashing with obstacles by turning to the proper angle while moving. The Fuzzy Logic algorithm has proven a commendable solution in dealing with certain control problems when the situation is ambiguous. One of the main difficulties faced by conventional control systems is the inability to operate in a condition with incomplete and imprecise information. As the complexity of a situation increases, a traditional mathematical model will be difficult if not impossible to implement. Fuzzy Logic is a tool for modeling uncertain systems by facilitating common sense reasoning in decision-making in the absence of complete and precise information. In this paper, the controller of an autonomous mobile robot is designed based on the theories of Fuzzy Logic. The wheeled robot is able to navigate by itself in a completely unstructured environment. The codes of MRC has written for implementing the separate modules of the Fuzzifier, Fuzzy Rule Base, Inference mechanism and Defuzzifier as hardware blocks. A behavioral model of MRC algorithm is first developed in MATLAB session with numerous data to evaluate its algorithm functionality. The development of MATLAB codes has converted into VHDL codes; for hardware implementation. Comparison results between MATLAB and VHDL of MRC algorithm also presented. Then the VHDL codes are synthesized using synthesis tool, known as Quartus II. Finally the MRC hardware blocks for VLSI design have been carried out. IEEE 2006-12 Book Section NonPeerReviewed text en http://shdl.mmu.edu.my/2133/1/Design%20and%20Synthesis%20of%20Mobile%20Robot%20Controller%20using%20Fuzzy.pdf Islam, Md. Shabiul and Azim, Md. Anwarul and Jahan, Md. Saukat and Othman, Masuri (2006) Design and Synthesis of Mobile Robot Controller using Fuzzy. In: 2006 IEEE International Conference on Semiconductor Electronics. IEEE, pp. 825-829. ISBN 0-7803-9730-4 http://dx.doi.org/10.1109/SMELEC.2006.380752 doi:10.1109/SMELEC.2006.380752 doi:10.1109/SMELEC.2006.380752
spellingShingle QA Mathematics
Islam, Md. Shabiul
Azim, Md. Anwarul
Jahan, Md. Saukat
Othman, Masuri
Design and Synthesis of Mobile Robot Controller using Fuzzy
title Design and Synthesis of Mobile Robot Controller using Fuzzy
title_full Design and Synthesis of Mobile Robot Controller using Fuzzy
title_fullStr Design and Synthesis of Mobile Robot Controller using Fuzzy
title_full_unstemmed Design and Synthesis of Mobile Robot Controller using Fuzzy
title_short Design and Synthesis of Mobile Robot Controller using Fuzzy
title_sort design and synthesis of mobile robot controller using fuzzy
topic QA Mathematics
url http://shdl.mmu.edu.my/2133/
http://shdl.mmu.edu.my/2133/
http://shdl.mmu.edu.my/2133/
http://shdl.mmu.edu.my/2133/1/Design%20and%20Synthesis%20of%20Mobile%20Robot%20Controller%20using%20Fuzzy.pdf