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 81–90 of 572 papers

TitleStatusHype
CaRtGS: Computational Alignment for Real-Time Gaussian Splatting SLAMCode2
Direct Multipath-Based SLAM—0
Neural Implicit Representation for Highly Dynamic LiDAR Mapping and Odometry—0
BlinkTrack: Feature Tracking over 100 FPS via Events and Images—0
Event-based Stereo Depth Estimation: A SurveyCode2
Exploring the potential of collaborative UAV 3D mapping in Kenyan savanna for wildlife research—0
Initialization of Monocular Visual Navigation for Autonomous Agents Using Modified Structure from Small Motion—0
Spectral Graph Theoretic Methods for Enhancing Network Robustness in Robot Localization—0
SPAQ-DL-SLAM: Towards Optimizing Deep Learning-based SLAM for Resource-Constrained Embedded Platforms—0
Bundle Adjustment in the Eager Mode—0
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