PLL-VO： An Efficient and Robust Visual Odometry Integrating Point-Line Features and Neural Networks

PLL-VO： An Efficient and Robust Visual Odometry Integrating Point-Line Features and Neural Networks

Visual odometry is crucial for the navigation and planning of autonomous robots, but low-light conditions, dramatic lighting changes, and low-texture scenes pose significant challenges to odometry estimation. This paper proposes PLL-VO, which integrates point-line features and deep learning. To over...

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Bibliographic Details
Main Authors: L. Zhao, Y. Yang, D. Ma, X. Lin, W. Wang
Format: Article
Language:English
Published: Copernicus Publications 2025-07-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-annals.copernicus.org/articles/X-G-2025/1045/2025/isprs-annals-X-G-2025-1045-2025.pdf
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