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 191–200 of 572 papers

TitleStatusHype
Dense RGB SLAM with Neural Implicit Maps—0
A Neurosymbolic Approach to Adaptive Feature Extraction in SLAM—0
Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations—0
Dense monocular Simultaneous Localization and Mapping by direct surfel optimization—0
Autonomous Navigation in Dynamic Environments: Deep Learning-Based Approach—0
Degenerate Motions in Multicamera Cluster SLAM with Non-overlapping Fields of View—0
Degeneracy in Self-Calibration Revisited and a Deep Learning Solution for Uncalibrated SLAM—0
Autonomous Asteroid Characterization Through Nanosatellite Swarming—0
Anchor Distance for 3D Multi-Object Distance Estimation from 2D Single Shot—0
A Collaborative Visual SLAM Framework for Service Robots—0
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