The Kalman filter: an introduction to concepts
Autonomous robot vehicles
Illumination Planning for Object Recognition Using Parametric Eigenspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Monte Carlo localization: efficient position estimation for mobile robots
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Robust recognition using eigenimages
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Zero Phase Representation of Panoramic Images for Image Vased Localization
CAIP '99 Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns
Robust Localization Using Panoramic View-Based Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Illumination insensitive recognition using eigenspaces
Computer Vision and Image Understanding
Karhunen-Loeve expansion of a set of rotated templates
IEEE Transactions on Image Processing
Active single landmark based global localization of autonomous mobile robots
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
| Hi-index | 0.00 |
We propose to use a robust method for appearance-based matching that has been shown to be insensitive to illumination and occlusion for robot self-localization. The drawback of this method is that it relies on panoramic images taken in one certain orientation, restricts the heading of the robot throughout navigation or needs additional sensors for orientation, e.g. a compass. To avoid these problems we propose a combination of the appearance-based method with odometry data. We demonstrate the robustness of the proposed self-localization against changes in illumination by experimental results obtained in the RoboCup Middle-Size scenario.