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 231–240 of 572 papers

TitleStatusHype
Closing the Loop: Graph Networks to Unify Semantic Objects and Visual Features for Multi-object Scenes—0
Evaluation of the Robustness of Visual SLAM Methods in Different Environments—0
Hyperspectral 3D Mapping of Underwater Environments—0
ICP Algorithm: Theory, Practice And Its SLAM-oriented Taxonomy—0
Improved Real-Time Monocular SLAM Using Semantic Segmentation on Selective Frames—0
Improving Autonomous Vehicle Mapping and Navigation in Work Zones Using Crowdsourcing Vehicle Trajectories—0
Evaluation and comparison of eight popular Lidar and Visual SLAM algorithms—0
Inclusive STEAM Education: A Framework for Teaching Cod-2 ing and Robotics to Students with Visually Impairment Using 3 Advanced Computer Vision—0
Closing the Calibration Loop: An Inside-out-tracking Paradigm for Augmented Reality in Orthopedic Surgery—0
ADD-SLAM: Adaptive Dynamic Dense SLAM with Gaussian Splatting—0
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