FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance
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Summary
A probabilistic approach to the problem of recognizing places based on their appearance that can determine that a new observation comes from a previously unseen place, and so augment its map, and is particularly suitable for online loop closure detection in mobile robotics.
- Type
- article
- Published
- 2008-06-01
- Cited by
- 1,614
- References
- 49
- OpenAlex
- https://openalex.org/W2144824356
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17969052
Keywords
Probabilistic logic, Artificial intelligence, Aliasing, Robotics, Computer science
References
- Localisation using an image-map
- Maximum likelihood bounded tree-width Markov networks
- An Introduction to Variational Methods for Graphical Models
- An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High-Dimensional Sparse Data
- The PageRank Citation Ranking : Bringing Order to the Web
- Incremental mapping of large cyclic environments
- Detecting Loop Closure with Scene Sequences
- A probabilistic model for appearance-based robot localization
- Appearance-Based Topological Bayesian Inference for Loop-Closing Detection in a Cross-Country Environment
- A Rao-Blackwellized particle filter for topological mapping
- Learning with mixtures of trees
- Deriving and matching image fingerprint sequences for mobile robot localization
- Visual odometry and map correlation
- Vision-based global localization and mapping for mobile robots
- Supervised Learning of Places from Range Data using AdaBoost
- Probabilistic Appearance Based Navigation and Loop Closing
- Object recognition from local scale-invariant features
- Probabilistic location recognition using reduced feature set
- Scalable Recognition with a Vocabulary Tree
- Context-based vision system for place and object recognition
Cited by
- Feature-based visual odometry and featureless place recognition for SLAM in 2.5D environments
- Image based exploration for indoor environments using local features
- Loop detection and extended target tracking using laser data
- Loop closure detection on a suburban road network using a continuous appearance-based trajectory
- Semantic Mapping with Mobile Robots
- Learning and acting in unknown and uncertain worlds
- Contributions to Localization, Mapping and Navigation in Mobile Robotics
- Visual SLAM for Measurement and Augmented Reality in Laparoscopic Surgery
- From local visual homing towards navigation of autonomous cleaning robots
- Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR
- A Comparison of Similarity Measures for Localization with Passive RFID Fingerprints
- Developing grounded representations for robots through the principles of sensorimotor coordination
- Contributions to the use of 3D lidars for autonomous navigation: calibration and qualitative localization. (Contributions à l'exploitation de lidar 3D pour la navigation autonome : calibrage et localisation qualitative)
- Towards robust night and day place recognition using visible and thermal imaging
- A Vision-Based Relative Navigation Approach for Autonomous Multirotor Aircraft
- Visual navigation for mobile robots using the Bag-of-Words algorithm
- Simultaneous localisation and mapping with prior information
- Plane-based 3D Mapping for Structured Indoor Environment
- Active Visual SLAM with Exploration for Autonomous Underwater Navigation
- Visual Localization Using Global Visual Features and Vanishing Points
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