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 231–240 of 572 papers

TitleStatusHype
A Geometric Nonlinear Stochastic Filter for Simultaneous Localization and Mapping—0
GRIHA: Synthesizing 2-Dimensional Building Layouts from Images Captured using a Smart Phone—0
GPO: Global Plane Optimization for Fast and Accurate Monocular SLAM Initialization—0
ICP Algorithm: Theory, Practice And Its SLAM-oriented Taxonomy—0
Improved Real-Time Monocular SLAM Using Semantic Segmentation on Selective Frames—0
Improving Autonomous Vehicle Mapping and Navigation in Work Zones Using Crowdsourcing Vehicle Trajectories—0
Data Fusion for Radio Frequency SLAM with Robust Sampling—0
Inclusive STEAM Education: A Framework for Teaching Cod-2 ing and Robotics to Students with Visually Impairment Using 3 Advanced Computer Vision—0
Data Fusion for Multipath-Based SLAM: Combining Information from Multiple Propagation Paths—0
RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Network—0
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