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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 221–230 of 572 papers

TitleStatusHype
DSMNet: Deep High-precision 3D Surface Modeling from Sparse Point Cloud Frames—0
Point-SLAM: Dense Neural Point Cloud-based SLAMCode2
LSGDDN-LCD: An Appearance-based Loop Closure Detection using Local Superpixel Grid Descriptors and Incremental Dynamic Nodes—0
USTC FLICAR: A Sensors Fusion Dataset of LiDAR-Inertial-Camera for Heavy-duty Autonomous Aerial Work Robots—0
Live image-based neurosurgical guidance and roadmap generation using unsupervised embedding—0
Photometric LiDAR and RGB-D Bundle AdjustmentCode0
Object-based SLAM utilizing unambiguous pose parameters considering general symmetry types—0
Millimeter Wave Wireless Communication Assisted Three-Dimensional Simultaneous Localization and Mapping—0
Visual Perception System for Autonomous Driving—0
Prediction of SLAM ATE Using an Ensemble Learning Regression Model and 1-D Global Pooling of Data Characterization—0
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