Vision-Based Gate Detection (YOLOv5)

Developed a vision-based gate detection system using YOLOv5 for autonomous drone racing. Fine-tuned the model on custom drone racing gate datasets and implemented lightweight post-processing algorithms to achieve robust real-time localization. The system handles varying lighting conditions, motion blur, and perspective distortions common in high-speed flight scenarios.