DocumentCode
2938180
Title
2D simultaneous localization and mapping for unmanned aerial vehicles
Author
Kök, Mehmet ; Barshan, Billur
Author_Institution
Elektrik ve Elektron. Muhendisligi Bolumu, Bilkent Univ., Ankara
fYear
2008
fDate
20-22 April 2008
Firstpage
1
Lastpage
4
Abstract
In this work, a 2D vision-based simultaneous localization and mapping algorithm is developed for an unmanned aerial vehicle flying at a constant altitude. We use visual features of images obtained from an on-board camera to identify different landmarks. Using these landmarks we apply the well-known extended Kalman filter to the SLAM problem and present some simulation results.
Keywords
Kalman filters; SLAM (robots); aerospace control; nonlinear filters; remotely operated vehicles; robot vision; 2D vision; SLAM; constant altitude; extended Kalman filter; landmark identification; onboard camera; simultaneous localization and mapping; unmanned aerial vehicle; visual image feature; Cameras; Kalman filters; Karhunen-Loeve transforms; Radar; Simultaneous localization and mapping; Sonar; Unmanned aerial vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, Communication and Applications Conference, 2008. SIU 2008. IEEE 16th
Conference_Location
Aydin
Print_ISBN
978-1-4244-1998-2
Electronic_ISBN
978-1-4244-1999-9
Type
conf
DOI
10.1109/SIU.2008.4632709
Filename
4632709
Link To Document