This project presents a sophisticated control system for an Automated Guided Vehicle (AGV). It integrates a variety of robotic principles and algorithms to offer a range of functionalities, including odometry, localization, path planning, and line following, all developed within the Robot Operating System (ROS) framework. Bellow we show the robot used.
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Odometry: Implements motion tracking of the AGV for accurate positioning.
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Kalman Filter: Employed for enhanced localization of the vehicle, ensuring precision in navigation. (Image bellow is obtained by simulation in matlab)
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Control to Reference Point: Enables the AGV to navigate and align with specific reference points. (Images bellow are obtained by simulation in matlab)
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Line Following: Features an algorithm that allows the AGV to follow a predefined line path.
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Path Planning using A*: Incorporates the A* algorithm for efficient and optimized path planning.(Image bellow is obtained by simulation in matlab)
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Python and ROS Integration: Developed in Python, the system communicates effectively with ROS, showcasing seamless integration and operation.
- Programming Language: Python, a powerful, flexible language known for its readability and ease of use.
- Framework: Robot Operating System (ROS), a flexible framework for writing robot software, offering a collection of tools, libraries, and conventions.
- Hardware: Raspberry Pi, a compact and affordable computer, connected to our PC using SSH for remote access and control.