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Vision-based Tracking of a Moving Ground Object by Quadcopter UAV using Noise Filtering

Anastasia Razinkova, Hyun-Chan Cho


Tracking of ground object using quadrotor unmanned aerial vehicles (UAVs) still remains challenging because of highly involved dynamics of quadrotor UAVs and the presence of large amounts of sensory and computed noise in the control system loop. This study proposes a visual servoing control system of a quadrotor UAV for tracking of a moving ground object. The proposed control system employs a single monocular camera to estimate object’s
position and allows to compensate for the noise introduced by the visual sensor by means of filtering. The proposed control strategy was verified through a series of computer simulations for various distinctive object motion trajectories and velocities. Implementation of the developed vision-based control system with noise filtering allowed to decrease object tracking error by 30%-60% depending on the object’s velocity. In addition, simulation results demonstrated that the developed control system allowed to increase the range of trackable object velocities, with the maximum tracking velocity increasing by 11% in case of a sharp turn as a result of filter implementation.


vision-based tracking, moving target, quadcopter, UAV, noise filtering.

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