On the representation and estimation of spatial uncertainly
International Journal of Robotics Research
The spatial semantic hierarchy
Artificial Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous Localization and Map-Building Using Active Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Simultaneous Localisation and Mapping with a Single Camera
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing
International Journal of Robotics Research
Fast incremental square root information smoothing
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Hierarchical SLAM: Real-Time Accurate Mapping of Large Environments
IEEE Transactions on Robotics
Toward a Unified Bayesian Approach to Hybrid Metric--Topological SLAM
IEEE Transactions on Robotics
iSAM: Incremental Smoothing and Mapping
IEEE Transactions on Robotics
LESS-mapping: Online environment segmentation based on spectral mapping
Robotics and Autonomous Systems
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Simultaneous Localization and Mapping (SLAM) suffers from a quadratic space and time complexity per update step. Recent advancements have been made in approximating the posterior by forcing the information matrix to remain sparse as well as exact techniques for generating the posterior in the full SLAM solution to both the trajectory and the map. Current approximate techniques for maintaining an online estimate of the map for a robot to use while exploring make capacity-based decisions about when to split into sub-maps. This paper will describe an alternative partitioning strategy for online approximate real-time SLAM which makes use of normalized graph cuts to remove less information from the full map.