Fast relocalisation and loop closing in keyframe-based SLAM

@article{MurArtal2014FastRA,
  title={Fast relocalisation and loop closing in keyframe-based SLAM},
  author={Raul Mur-Artal and Juan D. Tard{\'o}s},
  journal={2014 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2014},
  pages={846-853}
}
  • Raul Mur-Artal, J. D. Tardós
  • Published 29 September 2014
  • Computer Science
  • 2014 IEEE International Conference on Robotics and Automation (ICRA)
In this paper we present for the first time a relocalisation method for keyframe-based SLAM that can deal with severe viewpoint change, at frame-rate, in maps containing thousands of keyframes. As this method relies on local features, it permits the interoperability between cameras, allowing a camera to relocalise in a map built by a different camera. We also perform loop closing (detection + correction), at keyframerate, in loops containing hundreds of keyframes. For both relocalisation and… 
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References

SHOWING 1-10 OF 29 REFERENCES
Automatic Relocalization and Loop Closing for Real-Time Monocular SLAM
TLDR
The relocalization module can be used to recognize overlap in maps, i.e., when the camera has returned to a previously mapped area, and the system combining all of these abilities is able to map larger environments and for significantly longer periods than previous systems.
Improving the Agility of Keyframe-Based SLAM
TLDR
This paper presents two approaches to improving the agility of a keyframe-based SLAM system, and implements a very simple inter-frame rotation estimator to aid tracking when the camera is rapidly panning and enables a trivially simple yet effective relocalisation method.
Unified Loop Closing and Recovery for Real Time Monocular SLAM
TLDR
A unified method for recovering from tracking failure and closing loops in real time monocular simultaneous localisation and mapping, and a bag-of-words appearance model for ranking potential loop closures and a robust method for using both structure and image appearance to confirm likely matches.
Double window optimisation for constant time visual SLAM
We present a novel and general optimisation framework for visual SLAM, which scales for both local, highly accurate reconstruction and large-scale motion with long loop closures. We take a two-level
Robust monocular SLAM in dynamic environments
TLDR
A novel prior-based adaptive RANSAC algorithm (PARSAC) is proposed to efficiently remove outliers even when the inlier ratio is rather low, so that the camera pose can be reliably estimated even in very challenging situations.
Scale Drift-Aware Large Scale Monocular SLAM
TLDR
This paper describes a new near real-time visual SLAM system which adopts the continuous keyframe optimisation approach of the best current stereo systems, but accounts for the additional challenges presented by monocular input and presents a new pose-graph optimisation technique which allows for the efficient correction of rotation, translation and scale drift at loop closures.
Appearance-only SLAM at large scale with FAB-MAP 2.0
TLDR
A new formulation of appearance-only SLAM suitable for very large scale place recognition that incorporates robustness against perceptual aliasing and substantially outperforms the standard term-frequency inverse-document-frequency (tf-idf) ranking measure.
Temporally scalable visual SLAM using a reduced pose graph
TLDR
This paper demonstrates a system for temporally scalable visual SLAM using a reduced pose graph representation that uses new measurements to continually improve the map, yet achieves efficiency by avoiding adding redundant frames and not using marginalization to reduce the graph.
Parallel Tracking and Mapping for Small AR Workspaces
TLDR
A system specifically designed to track a hand-held camera in a small AR workspace, processed in parallel threads on a dual-core computer, that produces detailed maps with thousands of landmarks which can be tracked at frame-rate with accuracy and robustness rivalling that of state-of-the-art model-based systems.
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