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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 11–20 of 572 papers

TitleStatusHype
Gaussian-SLAM: Photo-realistic Dense SLAM with Gaussian SplattingCode3
SuperPoint-SLAM3: Augmenting ORB-SLAM3 with Deep Features, Adaptive NMS, and Learning-Based Loop ClosureCode2
Place Recognition: A Comprehensive Review, Current Challenges and Future DirectionsCode2
AQUA-SLAM: Tightly-Coupled Underwater Acoustic-Visual-Inertial SLAM with Sensor CalibrationCode2
FlexCloud: Direct, Modular Georeferencing and Drift-Correction of Point Cloud MapsCode2
Advancing Dense Endoscopic Reconstruction with Gaussian Splatting-driven Surface Normal-aware Tracking and MappingCode2
Open-Vocabulary Online Semantic Mapping for SLAMCode2
MBA-SLAM: Motion Blur Aware Dense Visual SLAM with Radiance Fields RepresentationCode2
ESVO2: Direct Visual-Inertial Odometry with Stereo Event CamerasCode2
CaRtGS: Computational Alignment for Real-Time Gaussian Splatting SLAMCode2
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