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 151–160 of 572 papers

TitleStatusHype
Deep Learning-based Cooperative LiDAR Sensing for Improved Vehicle Positioning—0
VOOM: Robust Visual Object Odometry and Mapping using Hierarchical LandmarksCode2
How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a SurveyCode5
Loopy-SLAM: Dense Neural SLAM with Loop Closures—0
Customizable Perturbation Synthesis for Robust SLAM BenchmarkingCode2
Particle Filter SLAM for Vehicle Localization—0
MoD-SLAM: Monocular Dense Mapping for Unbounded 3D Scene Reconstruction—0
SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAMCode3
Simultaneous Calibration and Navigation (SCAN) of Multiple Ultrasonic Local Positioning Systems—0
NeuV-SLAM: Fast Neural Multiresolution Voxel Optimization for RGBD Dense SLAM—0
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