This project involves a robotic arm powered by a Raspberry Pi, equipped with a camera that uses machine learning to identify and sort trash into three categories: paper, plastic, and metal. The application leverages TensorFlow Lite and OpenCV to enhance the robot's perception and sorting capabilities.
With the increasing amount of waste generated daily, efficient sorting of recyclables is crucial for sustainable waste management. This project aims to automate the sorting process, reducing human labor and improving recycling rates.
- Python: The main programming language used for application development.
- TensorFlow Lite: For machine learning model deployment.
- OpenCV: For image processing tasks.
- Raspberry Pi: The hardware platform for running the application and controlling the robotic arm.
To get started with this project, follow these steps:
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Clone the repository:
git clone https://github.com/ThibaMahlezana/Trash-sorting-Robot.git cd Trash-sorting-Robot -
Install dependencies: Ensure you have Python 3 installed, then install the required libraries:
pip install -r requirements.txt
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Setup the Raspberry Pi:
- Connect the robotic arm and camera to the Raspberry Pi.
- Configure the Raspberry Pi to allow access to the camera
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Run the application: Start the application by executing:
python main.py
- Place various types of trash in front of the robot's camera.
- The robot will identify the item and move it to the designated bin based on its classification (paper, plastic, or metal).
- Monitor the performance and accuracy through the console output.
This project is licensed under the MIT License. See the LICENSE file for details.
For inquiries or feedback, please reach out via:
- Email: thiba.ma@gmail.com
- Special thanks to the TensorFlow and OpenCV communities for their resources and support.
- Inspiration from various robotics and AI projects.