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 421–430 of 572 papers

TitleStatusHype
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction—0
3D Lidar Mapping Relative Accuracy Automatic Evaluation Algorithm—0
An FPGA Acceleration and Optimization Techniques for 2D LiDAR SLAM Algorithm—0
Privacy-Protection Drone Patrol System based on Face Anonymization—0
SLAM-Inspired Simultaneous Contextualization and Interpreting for Incremental Conversation Sentences—0
Maplets: An Efficient Approach for Cooperative SLAM Map Building Under Communication and Computation Constraints—0
Persistent Map Saving for Visual Localization for Autonomous Vehicles: An ORB-SLAM ExtensionCode1
Deep-Learning-Based Indoor Human Following of Mobile Robot Using Color Feature—0
Fast Geometric Surface based Segmentation of Point Cloud from Lidar Data—0
GPO: Global Plane Optimization for Fast and Accurate Monocular SLAM Initialization—0
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