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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 371–380 of 572 papers

TitleStatusHype
Embedded Vision for Self-Driving on Forest Roads—0
EndoFlow-SLAM: Real-Time Endoscopic SLAM with Flow-Constrained Gaussian Splatting—0
EndoGSLAM: Real-Time Dense Reconstruction and Tracking in Endoscopic Surgeries using Gaussian Splatting—0
Energy-Efficient SLAM via Joint Design of Sensing, Communication, and Exploration Speed—0
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs—0
Enhancing Feature Tracking Reliability for Visual Navigation using Real-Time Safety Filter—0
eSLAM: An Energy-Efficient Accelerator for Real-Time ORB-SLAM on FPGA Platform—0
Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methods—0
Evaluation and comparison of eight popular Lidar and Visual SLAM algorithms—0
Evaluation of the Robustness of Visual SLAM Methods in Different Environments—0
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