Topological mapping for mobile robots using a combination of sonar and vision sensing
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Localization and homing using combinations of model views
Artificial Intelligence - Special volume on computer vision
A layered architecture for office delivery robots
AGENTS '97 Proceedings of the first international conference on Autonomous agents
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
Experiences with an interactive museum tour-guide robot
Artificial Intelligence - Special issue on applications of artificial intelligence
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Invariant Features for Gray Scale Images
Mustererkennung 1995, 17. DAGM-Symposium
Omni-Directional Vision for Robot Navigation
OMNIVIS '00 Proceedings of the IEEE Workshop on Omnidirectional Vision
Markov localization using correlation
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Estimating the absolute position of a mobile robot using position probability grids
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Challenges of Image and Video Retrieval
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Qualitative vision-based path following
IEEE Transactions on Robotics - Special issue on rehabilitation robotics
A new pyramid-based color image representation for visual localization
Image and Vision Computing
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
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In this paper we present a vision-based approach to mobile robot localization, that integrates an image retrieval system with Monte-Carlo localization. The image retrieval process is based on features that are invariant with respect to image translations, rotations, and limited scale. Since it furthermore uses local features, the system is robust against distortion and occlusions which is especially important in populated environments. The sample-based Monte-Carlo localization technique allows our robot to efficiently integrate multiple measurements over time. Both techniques are combined by extracting for each image a set of possible view-points using a two-dimensional map of the environment. Our technique has been implemented and tested extensively using data obtained with a real robot. We present several experiments demonstrating the reliability and robustness of our approach.