Once it classifies the object, the Jetson-powered Airspace drone fires a tethered net to capture the other craft from the sky and safely returns it to its landing pad.
Airspace is the only drone security solution capable of identifying, tracking, and autonomously removing rogue drones from the sky.
The start-up is using GeForce GTX 1080 GPUs and DIGITS to train their deep learning model to detect anomalies in the sky and classify rogue drones. Once trained, the drone is equipped with an Jetson TX1 on-board, and uses VisionWorks, TensorRT and CUDA to classify and react to rogue drones in real-time.
Airspace is positioning the drone for use by law enforcement, governments, and even baseball stadiums to protect the athletes and fans from unwanted intruders.
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Autonomous Drone Hunts Down Rogue Drones From the Sky
Oct 18, 2016
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AI-Generated Summary
- Airspace deploys a drone security solution that identifies, tracks, and autonomously captures rogue drones using a tethered net.
- The system trains its deep learning detection model with DIGITS on GeForce GTX 1080 GPUs.
- Onboard inference runs on a Jetson TX1 module using VisionWorks, TensorRT, and CUDA for real-time classification and reaction.
- The technology targets law enforcement, government agencies, and venues such as baseball stadiums to protect people from unauthorized drone intrusions.
Next Step
- Read the Gizmodo article for additional details and demonstration footage.
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