Real-time vision-based tracking of a moving terrain target from Light Weight Fixed Wing UAV using gimbal control

被引:0
|
作者
Kumar, Prashant [1 ]
Sonkar, Sarvesh [1 ]
Ghosh, A. K. [2 ]
Philip, Deepu [3 ]
机构
[1] Indian Inst Technol, Kanpur 208016, Uttar Pradesh, India
[2] Indian Inst Technol, Aerosp Engn Dept, Kanpur 208016, Uttar Pradesh, India
[3] Indian Inst Technol, Ind Management & Engn, Kanpur 208016, Uttar Pradesh, India
关键词
Image Processing; Object Tracking; Field of view; Gimbal-Pointing; Geo-location; Centroid Tracking Algorithm;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, the use of unmanned aerial vehicles (UAVs) is widespread in urban traffic monitoring. However, the challenges faced while practical implementation from a fixed-wing UAV's involves compensating for the device vibration, real-time video transmission lag, small object sizes tracking while sending a command from Ground Control Station (GCS) to UAV and vice versa. The constantly changing position and orientation of UAV during different flight maneuvers lead to the loss of tracked objects from the field of view. The paper's primary objective is to develop a gimbal control algorithm for real-time object tracking and object location from a small-unmanned fixed-wing aircraft. The proposed algorithm deals with two scenarios, the first scenario offers gimbal pointing at a given coordinate, while second incorporates gimbal pointing such as to align the optical axis with a certain point in the image plane. The solution proposed is to turn the camera head in azimuth and elevation angles towards the object. The alternative suggested includes rotating the camera head in azimuth and elevation angles towards the object, and the suitable angles were calculated based on the camera's distance from the object, Global Positioning System (GPS) and Inertial Measurement Unit (IMU) (camera positioning and orientation) information. The algorithm was first simulated using MATLAB/Simulink using the same parameter of the actual aircraft UAV and further implemented in fixed-wing UAV. The result advocates the applicability of the algorithm and the future work to be done for robust object tracking.
引用
收藏
页码:154 / 159
页数:6
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