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 291–300 of 572 papers

TitleStatusHype
Indoor SLAM Using a Foot-mounted IMU and the local Magnetic Field—0
Sparse Image based Navigation Architecture to Mitigate the need of precise Localization in Mobile Robots—0
SelfTune: Metrically Scaled Monocular Depth Estimation through Self-Supervised Learning—0
Self-Supervised Domain Calibration and Uncertainty Estimation for Place RecognitionCode1
An Online Semantic Mapping System for Extending and Enhancing Visual SLAM—0
STUN: Self-Teaching Uncertainty Estimation for Place RecognitionCode1
Descriptellation: Deep Learned Constellation DescriptorsCode0
TwistSLAM: Constrained SLAM in Dynamic Environment—0
DL-SLOT: Dynamic Lidar SLAM and Object Tracking Based On Graph Optimization—0
SAGE: SLAM with Appearance and Geometry Prior for EndoscopyCode1
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