Vision-based localization methods under GPS-denied conditions
원문 초록
This paper reviews vision-based localization methods in GPS-denied environments and classifies the mainstream methods into Relative Vision Localization (RVL) and Absolute Vision Localization (AVL). For RVL, we discuss the broad application of optical flow in feature extraction-based Visual Odometry (VO) solutions and introduce advanced optical flow estimation methods. For AVL, we review recent advances in Visual Simultaneous Localization and Mapping (VSLAM) techniques, from optimization-based methods to Extended Kalman Filter (EKF) based methods. We also introduce the application of offline map registration and lane vision detection schemes to achieve Absolute Visual Localization. This paper compares the performance and applications of mainstream methods for visual localization and provides suggestions for future studies.
함께 살펴볼 논문
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SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment
EVLoc: Event-based Visual Localization in LiDAR Maps via Event-Depth Registration
Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry
eCARLA-scenes: A synthetically generated dataset for event-based optical flow prediction
EndoFlow-SLAM: Real-Time Endoscopic SLAM with Flow-Constrained Gaussian Splatting
UFM: A Simple Path towards Unified Dense Correspondence with Flow
토론
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