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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 276–300 of 572 papers

TitleStatusHype
Real-Time Monocular Object-Model Aware Sparse SLAM—0
Real-time Nonrigid Mosaicking of Laparoscopy Images—0
Reconfigurable Holographic Surface Aided Wireless Simultaneous Localization and Mapping—0
Reflex-Based Open-Vocabulary Navigation without Prior Knowledge Using Omnidirectional Camera and Multiple Vision-Language Models—0
Removing Dynamic Objects for Static Scene Reconstruction using Light Fields—0
Resilient Simultaneous Localization and Mapping Fusing Ultra Wide Band Range Measurements and Visual Odometry—0
Revisiting visual-inertial structure from motion for odometry and SLAM initialization—0
RGB-Depth SLAM Review—0
RGB-D Odometry and SLAM—0
RGB-D SLAM in Dynamic Environments Using Point Correlations—0
Exploring Object-Aware Attention Guided Frame Association for RGB-D SLAM—0
RISE-SLAM: A Resource-aware Inverse Schmidt Estimator for SLAM—0
Robust Large Scale Monocular Visual SLAM—0
Robust Monocular SLAM for Egocentric Videos—0
Robust Snapshot Radio SLAM—0
Rotational Outlier Identification in Pose Graphs Using Dual Decomposition—0
Rotation Averaging: A Primal-Dual Method and Closed-Forms in Cycle Graphs—0
S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization—0
S3-SLAM: Sparse Tri-plane Encoding for Neural Implicit SLAM—0
SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment—0
Scaffold-SLAM: Structured 3D Gaussians for Simultaneous Localization and Photorealistic Mapping—0
Scalable Structure From Motion for Densely Sampled Videos—0
SD-6DoF-ICLK: Sparse and Deep Inverse Compositional Lucas-Kanade Algorithm on SE(3)—0
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance—0
Segway DRIVE Benchmark: Place Recognition and SLAM Data Collected by A Fleet of Delivery Robots—0
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