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Simultaneous Localization and Mapping

Simultaneous localization and mapping (SLAM) is the task of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

( Image credit: ORB-SLAM2 )

Papers

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Showing 481–490 of 572 papers

TitleStatusHype
BAD SLAM: Bundle Adjusted Direct RGB-D SLAM—0
Direct Sparse MappingCode0
Continuous Direct Sparse Visual Odometry from RGB-D ImagesCode0
Spiking Neural Network on Neuromorphic Hardware for Energy-Efficient Unidimensional SLAM—0
Incremental Visual-Inertial 3D Mesh Generation with Structural RegularitiesCode1
Sparse Depth Enhanced Direct Thermal-infrared SLAM Beyond the Visible Spectrum—0
Beyond Photometric Loss for Self-Supervised Ego-Motion EstimationCode0
GSLAM: A General SLAM Framework and BenchmarkCode0
UcoSLAM: Simultaneous Localization and Mapping by Fusion of KeyPoints and Squared Planar MarkersCode0
GEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping—0
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