International Journal of Computer Vision
3-D Scene Data Recovery Using Omnidirectional Multibaseline Stereo
International Journal of Computer Vision
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Robotics and Autonomous Systems
Information-based compact pose SLAM
IEEE Transactions on Robotics
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
IEEE Transactions on Robotics
Localization and Matching Using the Planar Trifocal Tensor With Bearing-Only Data
IEEE Transactions on Robotics
Spatial learning for navigation in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Long-term experiment using an adaptive appearance-based map for visual navigation by mobile robots
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
Long-term mapping and localization using feature stability histograms
Robotics and Autonomous Systems
Experience-based navigation for long-term localisation
International Journal of Robotics Research
Robust loop closing over time for pose graph SLAM
International Journal of Robotics Research
Localization and navigation of the CoBots over long-term deployments
International Journal of Robotics Research
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Real-world environments such as houses and offices change over time, meaning that a mobile robot's map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metric-topological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.