Robust regression and outlier detection
Robust regression and outlier detection
Estimating uncertain spatial relationships in robotics
Autonomous robot vehicles
International Journal of Computer Vision
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Image-based 3D modeling: modeling from reality
Confluence of computer vision and computer graphics
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Simultaneous Localization and Map-Building Using Active Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A unifying framework for structure and motion recovery from image sequences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
Thin Junction Tree Filtering for Simultaneous Localization and Mapping
Thin Junction Tree Filtering for Simultaneous Localization and Mapping
Real-Time Simultaneous Localisation and Mapping with a Single Camera
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Visual Modeling with a Hand-Held Camera
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Thin junction tree filters for simultaneous localization and mapping
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A multilevel relaxation algorithm for simultaneous localization and mapping
IEEE Transactions on Robotics
Vision-based global localization and mapping for mobile robots
IEEE Transactions on Robotics
Exactly Sparse Delayed-State Filters for View-Based SLAM
IEEE Transactions on Robotics
Covariance recovery from a square root information matrix for data association
Robotics and Autonomous Systems
Surveying noctural cuttlefish camouflage behaviour using an AUV
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
Pose-graph visual SLAM with geometric model selection for autonomous underwater ship hull inspection
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Information-based compact pose SLAM
IEEE Transactions on Robotics
International Journal of Robotics Research
3-D motion estimation by integrating visual cues in 2-D multi-modal opti-acoustic stereo sequences
Computer Vision and Image Understanding
Approximate robotic mapping from sonar data by modeling perceptions with antonyms
Information Sciences: an International Journal
Color-accurate underwater imaging using perceptual adaptive illumination
Autonomous Robots
Fast topology estimation for image mosaicing using adaptive information thresholding
Robotics and Autonomous Systems
Inference on networks of mixtures for robust robot mapping
International Journal of Robotics Research
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This paper describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of underwater vehicles while exploiting the inertial sensor information that is routinely available on such platforms. We present a novel strategy for efficiently accessing and maintaining consistent covariance bounds within a SLAM information filter, thereby greatly increasing the reliability of data association. The technique is based upon solving a sparse system of linear equations coupled with the application of constant-time Kalman updates. The method is shown to produce consistent covariance estimates suitable for robot planning and data association. Real-world results are reported for a vision-based, six degree of freedom SLAM implementation using data from a recent survey of the wreck of the RMS Titanic.