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 271–280 of 572 papers

TitleStatusHype
VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition—0
SLAM for Multiple Extended Targets using 5G Signal—0
Stereo Visual Odometry with Deep Learning-Based Point and Line Feature Matching using an Attention Graph Neural Network—0
Tightly-Coupled LiDAR-Visual SLAM Based on Geometric Features for Mobile Agents—0
KP2Dtiny: Quantized Neural Keypoint Detection and Description on the EdgeCode0
PEBO-SLAM: Observer design for visual inertial SLAM with convergence guarantees—0
Investigation of the Challenges of Underwater-Visual-Monocular-SLAM—0
How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers—0
Towards View-invariant and Accurate Loop Detection Based on Scene Graph—0
FEDORA: Flying Event Dataset fOr Reactive behAvior—0
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