Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Predicting the Performance of Cooperative Simultaneous Localization and Mapping (C-SLAM)
International Journal of Robotics Research
Recovering Surface Layout from an Image
International Journal of Computer Vision
LabelMe: A Database and Web-Based Tool for Image Annotation
International Journal of Computer Vision
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving the Agility of Keyframe-Based SLAM
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Video-rate localization in multiple maps for wearable augmented reality
ISWC '08 Proceedings of the 2008 12th IEEE International Symposium on Wearable Computers
Parallel Tracking and Mapping on a camera phone
ISMAR '09 Proceedings of the 2009 8th IEEE International Symposium on Mixed and Augmented Reality
Communications of the ACM
Distributed Service-Oriented Robotics
IEEE Internet Computing
Wide-area augmented reality using camera tracking and mapping in multiple regions
Computer Vision and Image Understanding
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Robots with their heads in the clouds
IEEE Spectrum
Dense reconstruction on-the-fly
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Live tracking and mapping from both general and rotation-only camera motion
ISMAR '12 Proceedings of the 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
Vision-based place recognition: how low can you go?
International Journal of Robotics Research
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The Simultaneous Localization And Mapping by an autonomous mobile robot-known by its acronym SLAM-is a computationally demanding process for medium and large-scale scenarios, in spite of the progress both in the algorithmic and hardware sides. As a consequence, a robot with SLAM capabilities has to be equipped with the latest computers whose weight and power consumption might limit its autonomy. This paper describes a visual SLAM system based on a distributed framework where the expensive map optimization and storage is allocated as a service in the Cloud, while a light camera tracking client runs on a local computer. The robot onboard computers are freed from most of the computation, the only extra requirement being an internet connection. The data flow from and to the Cloud is low enough to be supported by a standard wireless connection. The experimental section is focused on showing real-time performance for single-robot and cooperative SLAM using an RGBD camera. The system provides the interface to a map database where: (1) a map can be built and stored, (2) stored maps can be reused by other robots, (3) a robot can fuse its map online with a map already in the database, and (4) several robots can estimate individual maps and fuse them together if an overlap is detected.