An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Eighteenth national conference on Artificial intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
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
The Graph SLAM Algorithm with Applications to Large-Scale Mapping of Urban Structures
International Journal of Robotics Research
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Springer Handbook of Robotics
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance
International Journal of Robotics Research
Map Matching and Data Association for Large-Scale Two-dimensional Laser Scan-based SLAM
International Journal of Robotics Research
The New College Vision and Laser Data Set
International Journal of Robotics Research
Robust and efficient robotic mapping
Robust and efficient robotic mapping
DP-SLAM: fast, robust simultaneous localization and mapping without predetermined landmarks
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Navigating, Recognizing and Describing Urban Spaces With Vision and Lasers
International Journal of Robotics Research
Visual topological SLAM and global localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Fast codebook generation by sequential data analysis for object classification
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
International Journal of Robotics Research
Vast-scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment
International Journal of Robotics Research
Persistent Navigation and Mapping using a Biologically Inspired SLAM System
International Journal of Robotics Research
Online and Incremental Appearance-based SLAM in Highly Dynamic Environments
International Journal of Robotics Research
Online probabilistic topological mapping
International Journal of Robotics Research
Appearance-only SLAM at large scale with FAB-MAP 2.0
International Journal of Robotics Research
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Toward a Unified Bayesian Approach to Hybrid Metric--Topological SLAM
IEEE Transactions on Robotics
Mapping a Suburb With a Single Camera Using a Biologically Inspired SLAM System
IEEE Transactions on Robotics
Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words
IEEE Transactions on Robotics
FrameSLAM: From Bundle Adjustment to Real-Time Visual Mapping
IEEE Transactions on Robotics
OpenRatSLAM: an open source brain-based SLAM system
Autonomous Robots
Vision-based place recognition: how low can you go?
International Journal of Robotics Research
Cleaning robot navigation using panoramic views and particle clouds as landmarks
Robotics and Autonomous Systems
Self-help: Seeking out perplexing images for ever improving topological mapping
International Journal of Robotics Research
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This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot's previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao-Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.