Stereo vision specific models for particle filter-based SLAM
Robotics and Autonomous Systems
Navigating, Recognizing and Describing Urban Spaces With Vision and Lasers
International Journal of Robotics Research
Real-time hierarchical outdoor SLAM based on stereovision and GPS fusion
IEEE Transactions on Intelligent Transportation Systems
Multi-robot visual SLAM using a Rao-Blackwellized particle filter
Robotics and Autonomous Systems
Simultaneous localization and mapping: A feature-based probabilistic approach
International Journal of Applied Mathematics and Computer Science - Special Section: Robot Control Theory Cezary Zielinski
1-point RANSAC for EKF-based structure from motion
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Undelayed initialization of line segments in monocular SLAM
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Visual Localization Using Ground Points
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Robotics and Autonomous Systems
Towards realtime handheld MonoSLAM in dynamic environments
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
iSAM2: Incremental smoothing and mapping using the Bayes tree
International Journal of Robotics Research
Mobile robot map building from time-of-flight camera
Expert Systems with Applications: An International Journal
Impact of Landmark Parametrization on Monocular EKF-SLAM with Points and Lines
International Journal of Computer Vision
Robust camera pose and scene structure analysis for service robotics
Robotics and Autonomous Systems
Cross-spectral visual simultaneous localization and mapping (SLAM) with sensor handover
Robotics and Autonomous Systems
Jointly compatible pair linking for visual tracking with probabilistic priors
ACSC '11 Proceedings of the Thirty-Fourth Australasian Computer Science Conference - Volume 113
Multi-view dense 3D modelling of untextured objects from a moving projector-cameras system
Machine Vision and Applications
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In this paper, we describe a system that can carry out simultaneous localization and mapping (SLAM) in large indoor and outdoor environments using a stereo pair moving with 6 DOF as the only sensor. Unlike current visual SLAM systems that use either bearing-only monocular information or 3-D stereo information, our system accommodates both monocular and stereo. Textured point features are extracted from the images and stored as 3-D points if seen in both images with sufficient disparity, or stored as inverse depth points otherwise. This allows the system to map both near and far features: the first provide distance and orientation, and the second provide orientation information. Unlike other vision-only SLAM systems, stereo does not suffer from ldquoscale driftrdquo because of unobservability problems, and thus, no other information such as gyroscopes or accelerometers is required in our system. Our SLAM algorithm generates sequences of conditionally independent local maps that can share information related to the camera motion and common features being tracked. The system computes the full map using the novel conditionally independent divide and conquer algorithm, which allows constant time operation most of the time, with linear time updates to compute the full map. To demonstrate the robustness and scalability of our system, we show experimental results in indoor and outdoor urban environments of 210 m and 140 m loop trajectories, with the stereo camera being carried in hand by a person walking at normal walking speeds of 4--5 km/h.