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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 181–190 of 572 papers

TitleStatusHype
PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments—0
InCrowd-VI: A Realistic Visual-Inertial Dataset for Evaluating SLAM in Indoor Pedestrian-Rich Spaces for Human NavigationCode0
Moving Horizon Estimation for Simultaneous Localization and Mapping with Robust Estimation Error Bounds—0
Exploring Emerging Trends and Research Opportunities in Visual Place Recognition—0
An Expeditious Spatial Mean Radiant Temperature Mapping Framework using Visual SLAM and Semantic Segmentation—0
EvenNICER-SLAM: Event-based Neural Implicit Encoding SLAM—0
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance—0
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
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