Paper Info
Title
Robust visual lock-on and simultaneous localization for an unmanned aerial vehicle
Abstract
We present a method for simultaneously locking on to a ground target and estimating the position of an unmanned aerial vehicle (UAV) under countermeasure (CM) conditions, where sensors are prevented from successfully tracking a target. Owing to the limited payload and power of the UAVs, we employ a monocular camera and a global positioning system (GPS) to carry out vision-based simultaneous localization and mapping (SLAM) using both an unscented Kalman filter and a Kalman filter. Since this approach estimates the state of the UAV and the location of the target, we can estimate the position of the target in the image, even in the presence of CMs. Our experiments show that the proposed method successfully locks on to the target and estimates the state of the UAV.
Year
DOI
Venue
2010
10.1109/IROS.2010.5650725
IROS
Keywords
Field
DocType
global positioning system,target location,unscented kalman filter,robust visual lock-on,kalman filters,gps,monocular camera,unmanned aerial vehicle,slam,mobile robots,aircraft,vision-based simultaneous localization and mapping,aerospace robotics,sensor,position estimation,cameras,object detection,slam (robots),uav,position measurement,remotely operated vehicles,countermeasure,robot vision,simultaneous localization and mapping,kalman filter,design automation,solid modeling,sensors
Computer vision,Remotely operated underwater vehicle,Object detection,Computer science,Kalman filter,Artificial intelligence,Global Positioning System,Solid modeling,Simultaneous localization and mapping,Mobile robot,Payload
Conference
ISSN
ISBN
Citations 
2153-0858
978-1-4244-6674-0
2
PageRank 
References 
Authors
0.37
11
3
Name
Order
Citations
PageRank
Jihong Min1193.73
Yekeun Jeong2935.51
In So Kweon32795207.62