Covariance recovery from a square root information matrix for data association
Robotics and Autonomous Systems
Automatically and efficiently inferring the hierarchical structure of visual maps
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Probabilistic structure matching for visual SLAM with a multi-camera rig
Computer Vision and Image Understanding
Reduced state representation in delayed-state SLAM
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
3D mapping for urban service robots
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Normalized graph cuts for visual SLAM
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Information-based compact pose SLAM
IEEE Transactions on Robotics
Vast-scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment
International Journal of Robotics Research
SLAM in O(logn) with the Combined Kalman-Information Filter
Robotics and Autonomous Systems
Cooperative AUV Navigation using a Single Maneuvering Surface Craft
International Journal of Robotics Research
Line maps in cluttered environments
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Pure topological mapping in mobile robotics
IEEE Transactions on Robotics
Robotics and Autonomous Systems
Smoothing-based submap merging in large area SLAM
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Target tracking without line of sight using range from radio
Autonomous Robots
iSAM2: Incremental smoothing and mapping using the Bayes tree
International Journal of Robotics Research
Editors Choice Article: Visual SLAM: Why filter?
Image and Vision Computing
Laser and Radar Based Robotic Perception
Foundations and Trends in Robotics
International Journal of Robotics Research
Tutorial on quick and easy model fitting using the SLoM framework
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
Evolutionary computation for intelligent self-localization in multiple mobile robots based on SLAM
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
Active planning for underwater inspection and the benefit of adaptivity
International Journal of Robotics Research
Gaussian Process Gauss-Newton for non-parametric simultaneous localization and mapping
International Journal of Robotics Research
Inference on networks of mixtures for robust robot mapping
International Journal of Robotics Research
Real-time 6-DOF multi-session visual SLAM over large-scale environments
Robotics and Autonomous Systems
International Journal of Robotics Research
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In this paper, we present incremental smoothing and mapping (iSAM), which is a novel approach to the simultaneous localization and mapping problem that is based on fast incremental matrix factorization. iSAM provides an efficient and exact solution by updating a QR factorization of the naturally sparse smoothing information matrix, thereby recalculating only those matrix entries that actually change. iSAM is efficient even for robot trajectories with many loops as it avoids unnecessary fill-in in the factor matrix by periodic variable reordering. Also, to enable data association in real time, we provide efficient algorithms to access the estimation uncertainties of interest based on the factored information matrix. We systematically evaluate the different components of iSAM as well as the overall algorithm using various simulated and real-world datasets for both landmark and pose-only settings.