DocumentCode :
3313906
Title :
Combined application of kalman filtering and correlation towards autonomous helicopter landing
Author :
Jan, Ibrar Ullah ; Khan, M. Umer ; Iqbal, Naeem
Author_Institution :
Dept. of Electr. Eng., Pakistan Inst. of Eng. & Appl. Sci., Islamabad
fYear :
2009
fDate :
17-18 Feb. 2009
Firstpage :
1
Lastpage :
6
Abstract :
Autonomous helicopter landing is a challenging problem in the field of aerial robotics. An autonomous maneuver depends largely on two capabilities: the decision of where to land and the generation of control signals to guide the vehicle to a safe landing. Here we present a control system that enables a helicopter to land on a stationary target (landmark) on the ground. The autonomous landing control process uses visual information to control the position, height as well as the orientation of the helicopter relative to the target for a safe and accurate landing. A remote controlled helicopter is used for the landing tests. The vision system, i.e., a wireless camera is mounted on the body of the helicopter and pointing downwards. The control algorithm is designed in MATLAB which issues control signals to the remote control of the helicopter based on the actual and desired visual inputs to the computer control system. The designed strategy of control is totally dynamics free as long as the helicopter and camera hardware´s are concern. The closed loop system is established through virtual feedback system having visual information. The application of Kalman filter (KF) is used for controlling the position and height of the helicopter. An individual controller is implemented for the orientation control based on the pattern-correlation of images.
Keywords :
Kalman filters; aerospace robotics; aerospace safety; aircraft landing guidance; cameras; closed loop systems; computer vision; correlation methods; feedback; helicopters; mathematics computing; mobile robots; object detection; remotely operated vehicles; Kalman filtering; MATLAB; UAV; aerial robotics; autonomous helicopter landing control; autonomous maneuver; closed loop system; correlation method; safe landing; target detection; unmanned aerial vehicle; virtual feedback system; vision system; wireless camera; Cameras; Control systems; Filtering; Helicopters; Kalman filters; Land vehicles; Remotely operated vehicles; Robots; Signal generators; Vehicle safety; Autonomous helicopter landing; computer control; dynamics free; kalman filter; pattern correlation; virtual feedback; vision system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer, Control and Communication, 2009. IC4 2009. 2nd International Conference on
Conference_Location :
Karachi
Print_ISBN :
978-1-4244-3313-1
Electronic_ISBN :
978-1-4244-3314-8
Type :
conf
DOI :
10.1109/IC4.2009.4909166
Filename :
4909166
Link To Document :
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