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High-Speed Interception Multicopter Control by Image-Based Visual Servoing
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AI
DOI：10.1109/TCST.2024.3451293.png)
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In recent years, reports of illegal drones threatening public safety have increased. For the invasion of fully autonomous drones, traditional methods, such as radio frequency interference and GPS shielding, may fail. This article proposes a scheme that uses an autonomous multicopter with a strapdown camera to intercept a maneuvering intruder unmanned aerial vehicle (UAV). The interceptor multicopter can autonomously detect and intercept intruders moving at high speed in the air. The strapdown camera avoids the complex mechanical structure of the electro-optical pod, making the interceptor multicopter compact. However, the coupling of the camera and multicopter motion makes interception tasks difficult. To solve this problem, an image-based visual servoing (IBVS) controller is proposed to make the interception fast and accurate. Then, in response to the time delay of sensor imaging and image processing relative to attitude changes in high-speed scenarios, a delayed Kalman filter (DKF) observer is generalized to predict the current image position and increase the update frequency. Finally, hardware-in-the-loop (HITL) simulations and outdoor flight experiments verify that this method has a high interception accuracy and success rate. In the flight experiments, a high-speed interception is achieved with a terminal speed of 20 m/s.
Keyword:
Drones
Cameras
Vectors
Delays
Observers
Visualization
Accuracy
Anti-drone system
delayed Kalman filter (DKF)
high-speed interception
image-based visual servoing (IBVS)
期刊
IF:
3.9
论文数:
4.9K
被引数:
1.7W
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