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An innovative method of detecting Unmanned Aerial Vehicles (UAVs) ispresented. The goal of this study is to develop a robust setup for anautonomous multi-rotor hunter UAV, capable of visually detecting and trackingthe intruder UAVs for real-time motion planning. The system consists of twoparts: object detection using a stereo camera to generate 3D point cloud dataand video tracking applying a Kalman filter for UAV motion modeling. Afterdetection, the hunter can aim and shoot a tethered net at the intruder toneutralize it. The computer vision, motion tracking, and planning algorithmscan be implemented on a portable computer installed on the hunter UAV.

Stereo Vision for Unmanned Aerial VehicleDetection, Tracking, and Motion Control