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
SLAM Endoscopy enhanced by adversarial depth prediction—0
SLAM for Indoor Mapping of Wide Area Construction Environments—0
SLAM for Multiple Extended Targets using 5G Signal—0
SLAM for Visually Impaired People: a Survey—0
SLAM-Inspired Simultaneous Contextualization and Interpreting for Incremental Conversation Sentences—0
SOS-Match: Segmentation for Open-Set Robust Correspondence Search and Robot Localization in Unstructured Environments—0
Space-Time Localization and Mapping—0
SPAQ-DL-SLAM: Towards Optimizing Deep Learning-based SLAM for Resource-Constrained Embedded Platforms—0
Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation—0
Sparse Depth Enhanced Direct Thermal-infrared SLAM Beyond the Visible Spectrum—0
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