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 321–330 of 572 papers

TitleStatusHype
Closing the Loop: Graph Networks to Unify Semantic Objects and Visual Features for Multi-object Scenes—0
Compositional Scalable Object SLAM—0
Construction Inspection through Spatial Database—0
Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection—0
Cooperative mmWave PHD-SLAM with Moving Scatterers—0
CP-SLAM: Collaborative Neural Point-based SLAM System—0
CudaSIFT-SLAM: multiple-map visual SLAM for full procedure mapping in real human endoscopy—0
cuVSLAM: CUDA accelerated visual odometry and mapping—0
DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environments—0
Data Fusion for Multipath-Based SLAM: Combining Information from Multiple Propagation Paths—0
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