Title :
An Autonomous Helicopter with Vision Based Navigation
Author :
Luo, Pei ; Pei, Hai-Long
Author_Institution :
South China Univ. of Technol., Guangzhou
fDate :
May 30 2007-June 1 2007
Abstract :
In this paper, we present an autonomous helicopter with vision based navigation called South China University of Technology unmanned aerial vehicle (SCUAV). A GPS/INS system has been designed and implemented for getting stable navigation information. A Kalman filtering has been used in this system for data fusion. A real-time computer vision system is presented in this paper as the complement of the GPS/INS system. The vision algorithm is designed and implemented in this paper, which is integrated with algorithms for tracking a known landmark and estimating the helicopter positions. A method of image processing is designed for tracking and recognizing known land marks. At the end of the paper, we will present the experiment results to demonstrate our efficacious algorithm.
Keywords :
Kalman filters; computer vision; helicopters; real-time systems; remotely operated vehicles; sensor fusion; Kalman filtering; autonomous helicopter; data fusion; real-time computer vision system; unmanned aerial vehicle; vision based navigation; Aircraft navigation; Algorithm design and analysis; Computer vision; Filtering; Global Positioning System; Helicopters; Kalman filters; Machine vision; Real time systems; Unmanned aerial vehicles;
Conference_Titel :
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-0818-4
Electronic_ISBN :
978-1-4244-0818-4
DOI :
10.1109/ICCA.2007.4376831
