AUTOMATED GUIDED ROBOT (AGR)

This project concerns the design and fabrication of the Automated Guided Robot (AGR) prototype, utilizing artificial intelligence (AI) and genetic algorithm (GA) as a mainframe in helping the robot to generate a self-understanding of the area of work and mobilization to a destination desired by t...

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Bibliographic Details
Main Author: Abd Rahim, Mohd Azlan Shah
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2007
Subjects:
Online Access:http://utpedia.utp.edu.my/9779/1/2007%20Bachelor%20-%20Autonomous%20Guided%20Robot%20%28AGR%29.pdf
http://utpedia.utp.edu.my/9779/
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Institution: Universiti Teknologi Petronas
Language: English
Description
Summary:This project concerns the design and fabrication of the Automated Guided Robot (AGR) prototype, utilizing artificial intelligence (AI) and genetic algorithm (GA) as a mainframe in helping the robot to generate a self-understanding of the area of work and mobilization to a destination desired by the user. The main objective of this project is to create and develop a Path Planning Mobile Robot able to avoid obstacles in its path and reach a target designated position from its starting point utilizing 3 wheel-based rover body, sensors, linear motors and microcontrollers. Compared to manual mobile robots, AGRs require sensors and control systems that generate feedback for the re-evaluation of an unexpected situation and to detect obstacles in the path the AGR is required to follow. The paper describes the network algorithms developed and used in the design process of the AGR including simulations and circuit designs done for the prototype. A general robotics circuit construction of the mainframe target board for central processing, a controller board for the sensor feedbacks and a small base tri-wheeled structure has been fabricated by the author and continual troubleshooting and enhancement has been done for these components of the AGR. Algorithm conversion to C code programming has been done throughout the project for the obstacle avoidance and path planning algorithms based upon the GA platform ofAI.