Tello Drone — Senior Project

Project · Computer vision · Python · OpenCV · YOLO · DJI Tello

A Python control stack for the DJI Tello, using OpenCV and YOLO to track faces in real time and adjust the drone’s position based on a moving subject.

Face tracking in the loop

The project connects directly to the DJI Tello video stream, runs YOLO-based face detection via OpenCV, and then uses those detections to drive control signals. The drone attempts to keep a face centered in the frame by adjusting yaw, altitude, and distance.

System design

• Video frames pulled from the Tello via UDP and decoded in Python.
• Faces detected using YOLO + OpenCV; bounding box position used as a control signal.
• Control loop sends velocity and rotation commands back to the drone over its SDK.
• Safety and bounds checks to avoid overly aggressive movements.

Lessons & takeaways

This was a hands-on way to explore latency, feedback loops, and the difference between a model that “just detects” something and a full system that has to respond physically and safely.

Code: Face Tracker · Drone Object Detection