Intelligent path guidance robot for visually impaired assistance
Visually impaired has limited movement using the classic white cane. Currently, there are many designs for devices that can assist the blind moves better in unfamiliar environment. Then, controllers were applied in the devices’ system so that it can improve the system’s efficiency and accuracy in de...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd.
2015
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/49876/ http://irep.iium.edu.my/49876/ http://irep.iium.edu.my/49876/ http://irep.iium.edu.my/49876/1/49876_-_Intelligent_path_guidance_robot_for_visually_impaired_assistance.pdf |
| Summary: | Visually impaired has limited movement using the classic white cane. Currently, there are many designs for devices that can assist the blind moves better in unfamiliar environment. Then, controllers were applied in the devices’ system so that it can improve the system’s efficiency and accuracy in dealing with real-time situations. That’s when the intelligent system was introduced in the field to handle nonlinear process of the devices. The purpose of this study is to control steering angle system for an intelligent path guidance robot by using Fuzzy Logic Controller with MATLAB applications. The methods includes the designing of the fuzzy controller for the robot system using Fuzzy logic toolbox, SIMULINK implementation with the results, and the step responses of the system. The fuzzy controller was used to give output for the robot’s motor in terms of angle so it can be return back to its track. Two inputs for the system was introduced, error and change in error of the angle of the robot relative to the track given, while the output is the steering angle for the robot. Rule bases for the controller was developed based on the expert knowledge of the system which consist of 9 fuzzy rules. The step responses shows the overshoot, settling time, rise time and peak time after the implementation of the designed Fuzzy Logic Controller in the system. |
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