@inproceedings{7029601d18884f6a88bf4484922e3842,
title = "Visual servo control of unmanned aerial vehicles: An object tracking-based approach",
abstract = "This paper investigates the object following control problem for a low-cost quadrotor unmanned aerial vehicle (UAV). An object tracking-based approach is proposed. In this approach, the techniques of object tracking and visual servo control are efficiently combined to achieve the control objectives. To eliminate the impact of tracking target rotation during tracking model, an online learning method is proposed by learning the object size over different view at the desired distance. On the basis of this, an image-based visual servo control law is then designed to ensure that the quadrotor can track the moving target in real-time and keep the desired distance away from the object. The applicability of the proposed scheme is verified by flight experiments. It is demonstrated that the proposed algorithm is robust to rotary movement.",
keywords = "Object Following Control, Online Learning, Visual Servo Control, Visual Tracking",
author = "Jia Yang and Xing Huo and Bing Xiao and Zhenzhou Fu and Chaofan Wu and Yiran Wei",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 29th Chinese Control and Decision Conference, CCDC 2017 ; Conference date: 28-05-2017 Through 30-05-2017",
year = "2017",
month = jul,
day = "12",
doi = "10.1109/CCDC.2017.7979116",
language = "英语",
series = "Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3524--3528",
booktitle = "Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017",
}