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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 141–150 of 572 papers

TitleStatusHype
Language, Environment, and Robotic Navigation—0
MM3DGS SLAM: Multi-modal 3D Gaussian Splatting for SLAM Using Vision, Depth, and Inertial Measurements—0
GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAMCode2
CG-SLAM: Efficient Dense RGB-D SLAM in a Consistent Uncertainty-aware 3D Gaussian FieldCode2
EndoGSLAM: Real-Time Dense Reconstruction and Tracking in Endoscopic Surgeries using Gaussian Splatting—0
DBA-Fusion: Tightly Integrating Deep Dense Visual Bundle Adjustment with Multiple Sensors for Large-Scale Localization and MappingCode3
Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture EnvironmentsCode1
RGBD GS-ICP SLAMCode4
DVN-SLAM: Dynamic Visual Neural SLAM Based on Local-Global Encoding—0
A Belief Propagation Algorithm for Multipath-based SLAM with Multiple Map Features: A mmWave MIMO Application—0
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