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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 31–40 of 572 papers

TitleStatusHype
STAMICS: Splat, Track And Map with Integrated Consistency and Semantics for Dense RGB-D SLAM—0
GI-SLAM: Gaussian-Inertial SLAM—0
A Sigma Point-based Low Complexity Algorithm for Multipath-based SLAM in MIMO Systems—0
3D Densification for Multi-Map Monocular VSLAM in Endoscopy—0
DynaGSLAM: Real-Time Gaussian-Splatting SLAM for Online Rendering, Tracking, Motion Predictions of Moving Objects in Dynamic Scenes—0
AQUA-SLAM: Tightly-Coupled Underwater Acoustic-Visual-Inertial SLAM with Sensor CalibrationCode2
Inclusive STEAM Education: A Framework for Teaching Cod-2 ing and Robotics to Students with Visually Impairment Using 3 Advanced Computer Vision—0
On the Connection Between Magnetic-Field Odometry Aided Inertial Navigation and Magnetic-Field SLAM—0
DVM-SLAM: Decentralized Visual Monocular Simultaneous Localization and Mapping for Multi-Agent Systems—0
Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelinesCode1
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