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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 451–460 of 572 papers

TitleStatusHype
Fast Loop Closure Detection via Binary Content—0
Dense monocular Simultaneous Localization and Mapping by direct surfel optimization—0
Statistical Outlier Identification in Multi-robot Visual SLAM using Expectation Maximization—0
RGB-D Odometry and SLAM—0
Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey—0
Kernel learning for visual perceptionCode0
SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation—0
Tigris: Architecture and Algorithms for 3D Perception in Point CloudsCode0
Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM—0
Exactly Sparse Gaussian Variational Inference with Application to Derivative-Free Batch Nonlinear State Estimation—0
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