Autonomous target tracking of a quadrotor uav using monocular visual-inertial odometry
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Date
2018-06
Authors
Chin Mun Xue
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Abstract
Unmanned Aerial Vehicle (UAV) has been finding its ways into different applications.
Hence, recent years witness extensive research towards achieving higher autonomy in
UAV. Computer Vision (CV) algorithms replace Global Navigation Satellite System
(GNSS), which is not reliable when the weather is bad, inside buildings or at secluded
areas in performing real-time pose estimation. The controller later uses the pose to
navigate the UAV. This project presents a simulation of UAV, in MATLAB &
SIMULINK, capable of autonomously detecting and tracking a designed visual marker.
Referring to and improving the state-of-the-art CV algorithms, there is a newly
formulated approach to detect the designed visual marker. The combination of data from
the monocular camera with that from Inertial Measurement Unit (IMU) and sonar sensor
enables the pose estimation of the UAV relative to the designed visual marker. A
Proportional-Integral-Derivative (PID) controller later uses the pose of the UAV to
navigate itself to be always following the target of interest.