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 331–340 of 572 papers

TitleStatusHype
VI-SLAM2tag: Low-Effort Labeled Dataset Collection for Fingerprinting-Based Indoor Localization—0
VECtor: A Versatile Event-Centric Benchmark for Multi-Sensor SLAM—0
Wireless Channel Prediction in Partially Observed Environments—0
Automated Wheat Disease Detection using a ROS-based Autonomous Guided UAV—0
Data Fusion for Radio Frequency SLAM with Robust Sampling—0
ICP Algorithm: Theory, Practice And Its SLAM-oriented Taxonomy—0
Extracting Zero-shot Common Sense from Large Language Models for Robot 3D Scene Understanding—0
S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization—0
PMBM-based SLAM Filters in 5G mmWave Vehicular Networks—0
Indoor simultaneous localization and mapping based on fringe projection profilometry—0
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