SkyXel Robotic Team A project by the SkyXel Robotic Team aiming to develop advanced robotic solutions for the Fira Autonomous Race(Air) competition.
The FiraAirPro2025 project is developed by the SkyXel Robotic Team. This project focuses on building innovative robotic solutions to compete in the Fira Autonomous Race(Air) competition.
The main task of the FiraAirPro2025 competition is divided into two key parts. The first part involves gate detection and alignment of the drone to successfully pass through rectangular gates. This requires accurate visual processing and precise control to ensure the drone navigates through each gate efficiently.
The second part focuses on line detection and following. In this phase, the drone must detect a track line on the ground and autonomously follow it using real-time visual feedback and motion control algorithms.
These challenges were addressed using multithreaded processing and classical computer vision techniques. By separating image processing and control tasks into parallel threads, the system ensures real-time performance and responsiveness.
Additionally, the drone is controlled using a PID (Proportional-Integral-Derivative) controller, which provides smooth and stable flight behavior while navigating through gates and following lines.
To get a local copy up and running follow these simple steps.
- Clone the repo
git clone https://github.com/Zahra-Mazinani/FiraAirPro2025.git pip install -r requirements.txt
If you don't have access to a Tello drone or can't run the code with the actual device, you can use the FakeTello module instead of djitellopy to test and run the code without a drone. In that case, make sure to replace:
tello.Tello()with:
import fake_tello
fake_tello.FakeTello()-
First, connect your computer to the Wi-Fi network of the Tello drone. Execute the following script to start the initial color filtering process:
python extra_files/color_filter.py
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After running the script, open the config file and fine-tune the HSV filter parameters based on your environment and lighting conditions.
To run the gate traversal code, you can use the following command:
python gate_follower/main.py
- Implement logging and better error handling
- Add search patterns to find gates or line
- Write better documentation and usage examples
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you fork this project and participate in a competition using it, please make sure to share all your modified code after the competition, in accordance with the GPL license. Sharing your improvements helps others learn and benefits the entire community.
This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.
Zahra Babaei - LinkedIn - Email
Zahra Mazinani - LinkedIn - Email
Project Link: https://github.com/Zahra-Mazinani/FiraAirPro2025