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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 572 papers

TitleStatusHype
ecg2o: A Seamless Extension of g2o for Equality-Constrained Factor Graph OptimizationCode0
vS-Graphs: Integrating Visual SLAM and Situational Graphs through Multi-level Scene Understanding—0
FGS-SLAM: Fourier-based Gaussian Splatting for Real-time SLAM with Sparse and Dense Map Fusion—0
From Gaming to Research: GTA V for Synthetic Data Generation for Robotics and Navigations—0
Enhancing Feature Tracking Reliability for Visual Navigation using Real-Time Safety Filter—0
FlexCloud: Direct, Modular Georeferencing and Drift-Correction of Point Cloud MapsCode2
Advancing Dense Endoscopic Reconstruction with Gaussian Splatting-driven Surface Normal-aware Tracking and MappingCode2
SSF-PAN: Semantic Scene Flow-Based Perception for Autonomous Navigation in Traffic Scenarios—0
GS-LIVO: Real-Time LiDAR, Inertial, and Visual Multi-sensor Fused Odometry with Gaussian Mapping—0
Self-Organizing Edge Computing Distribution Framework for Visual SLAM—0
Show:102550
← PrevPage 5 of 58Next →

No leaderboard results yet.