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 511–520 of 572 papers

TitleStatusHype
Deep Visual Odometry Methods for Mobile Robots—0
Towards an Embodied Semantic Fovea: Semantic 3D scene reconstruction from ego-centric eye-tracker videos—0
Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization—0
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs—0
Sensors, SLAM and Long-term Autonomy: A Review—0
Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation—0
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC—0
RGB-Depth SLAM Review—0
Visual Global Localization with a Hybrid WNN-CNN ApproachCode0
Position Estimation of Camera Based on Unsupervised Learning—0
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