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
Towards View-invariant and Accurate Loop Detection Based on Scene Graph—0
TwistSLAM: Constrained SLAM in Dynamic Environment—0
Unified Few-shot Crack Segmentation and its Precise 3D Automatic Measurement in Concrete Structures—0
Unified Representation of Geometric Primitives for Graph-SLAM Optimization Using Decomposed Quadrics—0
UP-SLAM: Adaptively Structured Gaussian SLAM with Uncertainty Prediction in Dynamic Environments—0
USTC FLICAR: A Sensors Fusion Dataset of LiDAR-Inertial-Camera for Heavy-duty Autonomous Aerial Work Robots—0
Variational Filtering with Copula Models for SLAM—0
VECtor: A Versatile Event-Centric Benchmark for Multi-Sensor SLAM—0
View Selection with Geometric Uncertainty Modeling—0
Vision-Aided Absolute Trajectory Estimation Using an Unsupervised Deep Network with Online Error Correction—0
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