SOTAVerified

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 291–300 of 572 papers

TitleStatusHype
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
Region Prediction for Efficient Robot Localization on Large MapsCode0
Task Space Control of Robot Manipulators based on Visual SLAM—0
NICER-SLAM: Neural Implicit Scene Encoding for RGB SLAM—0
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