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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 311–320 of 572 papers

TitleStatusHype
Set-Type Belief Propagation with Applications to Poisson Multi-Bernoulli SLAM—0
LSGDDN-LCD: An Appearance-based Loop Closure Detection using Local Superpixel Grid Descriptors and Incremental Dynamic Nodes—0
SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning—0
Simultaneous Calibration and Navigation (SCAN) of Multiple Ultrasonic Local Positioning Systems—0
Simultaneous Localization and Layout Model Selection in Manhattan Worlds—0
Simultaneous Localization and Mapping: Through the Lens of Nonlinear Optimization—0
Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR—0
Simultaneous Localization And Mapping with depth Prediction using Capsule Networks for UAVs—0
Simultaneous Localization, Mapping, and Manipulation for Unsupervised Object Discovery—0
SLAM-based Integrity Monitoring Using GPS and Fish-eye Camera—0
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