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 201–210 of 572 papers

TitleStatusHype
Robust Second-order LiDAR Bundle Adjustment Algorithm Using Mean Squared Group Metric—0
Experience Dependent Formation of Global Coherent Representation of Environment by Grid Cells and Head Direction Cells—0
Advances in Inference and Representation for Simultaneous Localization and Mapping—0
Exactly Sparse Gaussian Variational Inference with Application to Derivative-Free Batch Nonlinear State Estimation—0
GI-SLAM: Gaussian-Inertial SLAM—0
Global Pose Estimation with an Attention-based Recurrent Network—0
A Sigma Point-based Low Complexity Algorithm for Multipath-based SLAM in MIMO Systems—0
3D Scene Parsing via Class-Wise Adaptation—0
Active collaboration in relative observation for Multi-agent visual SLAM based on Deep Q Network—0
EvenNICER-SLAM: Event-based Neural Implicit Encoding SLAM—0
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