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Drone Vision Disruption

This study aims to create a 2-axis tracker system that can recognize drones and locate the position of the drone camera so that the laser beam can track and dazzle the drone camera. The depth camera is used to localize the part of the target and is created using the YOLOv5 algorithm as a deep learning detector model. Due to its small size, the drone camera is challenging to detect and calculate the detection range. The adaptive detection method approach combines drone detection and drone camera detection. The depth camera provides input in the form of a three-coordinate axis from the target

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Researcher

Prof. Richard Han, Prof. Judith Dawes, Prof. Rich Mildren, Dr. Phuc Nguyen, Dr. Endrowednes Kuantama, Yihao Zhang, Faiyaz Rahman, Tasnim Azad Abi

Our Partners

Photonics Research Centre, University of Texas at Arlington

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About Us

The Macquarie Drone Lab is an interdisciplinary research group with leading-edge autonomous drone systems and applications. Currently based at Macquarie University Sydney, our team consists of diverse researchers and students with the determination to advance the capabilities of novel drone applications and flight control systems.

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