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 11–20 of 572 papers

TitleStatusHype
SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAMCode3
3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and HumansCode2
GV-Bench: Benchmarking Local Feature Matching for Geometric Verification of Long-term Loop Closure DetectionCode2
GO-SLAM: Global Optimization for Consistent 3D Instant ReconstructionCode2
CG-SLAM: Efficient Dense RGB-D SLAM in a Consistent Uncertainty-aware 3D Gaussian FieldCode2
CaRtGS: Computational Alignment for Real-Time Gaussian Splatting SLAMCode2
Customizable Perturbation Synthesis for Robust SLAM BenchmarkingCode2
FlexCloud: Direct, Modular Georeferencing and Drift-Correction of Point Cloud MapsCode2
From Perfect to Noisy World Simulation: Customizable Embodied Multi-modal Perturbations for SLAM Robustness BenchmarkingCode2
General Place Recognition Survey: Towards Real-World AutonomyCode2
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