Abstract
Unmanned Aerial Vehicles (UAVs) have recently shown great performance collecting visual data through autonomous exploration and mapping, which are widely used in reconnaissance, surveillance, and target acquisition (RSTA) applications. In this paper, we present an onboard vision-based system for low-cost UAVs to autonomously track a moving target. Real-time visual tracking is achieved by using an object detection algorithm based on the Kernelized Correlation Filter (KCF) tracker. A 3-axis gimbaled camera with separate Inertial Measurement Unit (IMU) is used to aim at the selected target during flights. The flight control algorithm for tracking tasks is implemented on a customized quadrotor equipped with an onboard computer and a microcontroller. The proposed system is experimentally validated by successfully chasing a ground and aerial target in an outdoor environment, which has proven its reliability and efficiency.
Highlights
The past decade has witnessed an explosive growth in the utilization of unmanned aerial vehicles (UAVs), attracting more and more attention from research institutions around the world [1,2]
After selecting a target in the video streams, the gimbal system is activated and rotates the camera to point at the selected target, which can be regarded as a step response
The boresight error pixels are plotted in azimuth and elevation, respectively, which are printed on the top left of the screen
Summary
The past decade has witnessed an explosive growth in the utilization of unmanned aerial vehicles (UAVs), attracting more and more attention from research institutions around the world [1,2]. The takeoff weight of most quadrotors is less than 15 kg, so payload and battery endurance for onboard equipment are very limited In this situation, precisely and robustly tracking a moving target by using a small-scale UAV platform is still a challenging task because the onboard computational capability is poor and sensors are low-cost [17]. The restricted FOV of the camera makes it a challenging task to keep the fast-moving target in the image, which means the FOV constraints must be fully considered in the guidance law [47] To solve these problems, a gimbal system is widely used to provide inertial stability to the camera by isolating it from the UAV motion and vibration.
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