Machine Learning for Obstacle Avoidance
Train neural network for autonomous obstacle detection and avoidance.
Tutorials, guides, and tips for getting the most out of your FLYQ drone
Train neural network for autonomous obstacle detection and avoidance.
Connect PS4/Xbox controllers via Bluetooth for traditional RC control.
Complete step-by-step guide to flashing, updating, and troubleshooting FLYQ Air firmware using multiple methods for all experience levels.
Build your own flight controller code from scratch using Arduino.
Record flight data to SD card and analyze performance metrics.
Configure FLYQ for FPV racing with acro mode and low-latency controls.
Control drone with hand gestures detected through laptop webcam.
Use FLYQ Vision camera for photos, video streaming, and computer vision.
Program autonomous flight paths with GPS waypoints for FLYQ Vision.
Control your FLYQ drone using voice commands via mobile app.
Connect and read data from ultrasonic, IR, and environmental sensors.
Use barometric pressure sensor for stable altitude hold functionality.
Build custom web interface for controlling FLYQ from any browser.
Access accelerometer and gyroscope data for custom flight algorithms.
Write automated flight scripts with Python for takeoff, patterns, and landing.
Create stunning LED displays using Arduino code for FLYQ status lights.
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