JRFCQAI Arduino UNO-Q AI Autonomous Drone | Bench-HIL Props-Off Test

In this video, we demonstrate the Bench-HIL (Hardware-in-the-Loop) validation mode for the JRFCQAI Opensource AI Autonomous Drone System utilizing using Dual-Brain Architecture of Arduino UNO-Q. Bench-HIL mode provides a safe, props-off environment for testing flight controller logic, telemetry loops, and autonomous navigation without the risks of physical flight testing. = Hackster.io - Invent the Future with Arduino UNO Q and App Lab project entry = Developer: Ravi Butani and Madhuri Vaghasia| Track: Robotics Board: Arduino UNO Q (Qualcomm Dragonwing QRB2210 + STM32U585) Framework: JRFCQAI (Open-Source) Key Highlights in This Video Active Hardware Pipeline: Real-time sensor reading (MPU6050/MS5611 IMU data), live 400Hz motor PWM driving via Zephyr RTOS, and onboard camera stream processing via the Qualcomm® Dragonwing™ MPU. Closed-Loop Simulation: Emulating spatial displacement feedback (latitude, longitude, altitude) for multi-waypoint missions while physical motors respond dynamically on the bench. JRFCQAI Web GCS Integration: Real-Time Telemetry: 40-byte binary frame decoding (stm_tx_tel) with XOR validation for attitude, battery voltage, flight modes, and error tracking. Interactive Leaflet GIS Mapping: Waypoint route planning, polyline rendering, and automated 12-byte binary command frame (WP) execution. AI Flight & Object Detection: Onboard 640x480 video feed featuring target detection, bounding-box tracking, and automated altitude adjustments upon detecting target triggers. Manual Control Matrix & REST API: Fast control dispatching via a 3x4 command grid powered by a FastAPI/Uvicorn backend. Configuration Note To toggle between Bench-HIL Mode and Full Flight Mode, update the HIL mode flag inside send_telemetry.ino as detailed in the source code comments. = Open Source & Credits = This project is shared with the Arduino & Maker community to accelerate open-source edge-AI UAV research on UNO Q. Special thanks and attribution to Joop Broking for his foundational YMFC-32 Autonomous flight code. http://www.brokking.net/ymfc-32_auto_... Disclaimer: Experimental project created for research/educational purposes. Provided "AS IS" without warranty. Operating DIY drones involves risk—fly responsibly and at your own risk. = GitHub opensource project link = https://github.com/butaniravi/JRFCQAI