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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 551–560 of 572 papers

TitleStatusHype
Shared Coupling-bridge for Weakly Supervised Local Feature LearningCode0
Tigris: Architecture and Algorithms for 3D Perception in Point CloudsCode0
Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric ConstraintsCode0
LoopDB: A Loop Closure Dataset for Large Scale Simultaneous Localization and MappingCode0
BEyond observation: an approach for ObjectNavCode0
Visual-Inertial Monocular SLAM with Map ReuseCode0
AirLoop: Lifelong Loop Closure DetectionCode0
Backtracking Regression Forests for Accurate Camera RelocalizationCode0
A Scan-to-Locality Map Strategy for 2D LiDAR and RGB-D Data FusionCode0
Localization and Perception for Control and Decision Making of a Low Speed Autonomous Shuttle in a Campus Pilot DeploymentCode0
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