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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 241–250 of 572 papers

TitleStatusHype
Degenerate Motions in Multicamera Cluster SLAM with Non-overlapping Fields of View—0
Indoor simultaneous localization and mapping based on fringe projection profilometry—0
Indoor SLAM Using a Foot-mounted IMU and the local Magnetic Field—0
Indoor Smartphone SLAM with Learned Echoic Location Features—0
Inertial Guided Uncertainty Estimation of Feature Correspondence in Visual-Inertial Odometry/SLAM—0
Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations—0
eSLAM: An Energy-Efficient Accelerator for Real-Time ORB-SLAM on FPGA Platform—0
InpaintFusion: Incremental RGB-D Inpainting for 3D Scenes—0
CholecSeg8k: A Semantic Segmentation Dataset for Laparoscopic Cholecystectomy Based on Cholec80—0
Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM—0
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