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 1–10 of 572 papers

TitleStatusHype
Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR—0
Adaptive Multipath-Based SLAM for Distributed MIMO Systems—0
EndoFlow-SLAM: Real-Time Endoscopic SLAM with Flow-Constrained Gaussian Splatting—0
Posterior Cramér-Rao Bounds on Localization and Mapping Errors in Distributed MIMO SLAM—0
SuperPoint-SLAM3: Augmenting ORB-SLAM3 with Deep Features, Adaptive NMS, and Learning-Based Loop ClosureCode2
A Novel ViDAR Device With Visual Inertial Encoder Odometry and Reinforcement Learning-Based Active SLAM Method—0
LRSLAM: Low-rank Representation of Signed Distance Fields in Dense Visual SLAM System—0
Faster than Fast: Accelerating Oriented FAST Feature Detection on Low-end Embedded GPUs—0
LoopDB: A Loop Closure Dataset for Large Scale Simultaneous Localization and MappingCode0
Dy3DGS-SLAM: Monocular 3D Gaussian Splatting SLAM for Dynamic Environments—0
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