The Autonomous Litter Detection and Delivery System (ALDDS) is a capstone project aimed at developing an autonomous system for detecting and collecting litter in outdoor environments. The system utilizes computer vision techniques and robotics to identify and retrieve litter, contributing to the cleanliness and sustainability of public spaces.

• Autonomous navigation and exploration of outdoor environments
• Real-time litter detection using computer vision algorithms
• Efficient path planning for litter retrieval
• 3D printed Mantis-Claw for litter collection and delivery to designated bins
• User-friendly interface for system monitoring and control

1. Clone the repository:

   git clone https://github.com/TLAndrewMarkDale/CapstoneII_Group15_ALDDS.git

2. Install the required dependencies:

   pip install -r requirements.txt

3. Set up the necessary hardware components, including the robot platform, sensors, and actuators.

4. Configure the system parameters in the config.yaml file.

1. Connect To Tello Drone
2. Launch the ALDDS system: `ALDDS_gui.py`

2. Monitor the system's performance through the user interface.

3. Retrieve the collected litter from the designated bins.

Contributions to the ALDDS project are welcome! If you would like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them with descriptive messages.
4. Push your changes to your forked repository.
5. Submit a pull request detailing your changes.

This project is licensed under the MIT License.

For any questions or inquiries, please contact the project team:

• Andrew Mark Dale
• Andre Dallaire
• Nikhil Lohar
• Mayo Adebiyi