AI Ardupilot Drone Interceptor

I’m building a proof-of-concept drone interceptor that relies on the Ardupilot flight stack and an onboard AI module. The goal is clear: once airborne, the aircraft must identify other drones in its vicinity, lock on, then maintain a stable track and follow pattern—all without human stick time.

Core requirements
• Ardupilot will handle all flight control, so your work focuses on integrating the AI pipeline with its GUIDED modes and mavlink commands.
• The AI must deliver reliable, real-time object recognition that flags and classifies “drone” targets from the video feed, pushing bounding-box coordinates back to the flight controller at 20 Hz or better.
• On receipt of those coordinates, the autopilot should autonomously manoeuvre to keep the target centred, holding a safe standoff distance that I can configure via a parameter file.

Deliverables
1. Clean, well-documented code for the vision stack (Python/C++, OpenCV, TensorFlow or similar) plus a companion Ardupilot lua or mavlink-based script that interprets vision output and issues NAV commands.
2. A step-by-step setup guide covering hardware connections, firmware parameters, and any custom GStreamer pipelines required for the video link.
3. Short demo footage or SITL log proving that the system detects a drone-class object and keeps it in frame for at least 60 seconds.

Acceptance will be based on flawless compilation, smooth SITL tests, and a final field test on my quad running latest Ardupilot stable. If you’ve previously tied AI vision into PX4 or Ardupilot, let’s chat—I’m ready to move fast.