ArticleSensors (Basel, Switzerland)2024
LRPL-VIO: A Lightweight and Robust Visual-Inertial Odometry with Point and Line Features.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Scene-Adaptive Line-Aware Visual Measurement Conditioning for Stereo Visual-Inertial Odometry.Sensors (Basel, Switzerland) · 2026Article
- EDL-VINS: Protocol-Controlled Evaluation of an EDLines and Line-Flow Point-Line Visual-Inertial System.Sensors (Basel, Switzerland) · 2026Article
- Visual-Inertial Fusion Framework for Isolating Seated Human-Body Vibration in Dynamic Vehicular Environments.Sensors (Basel, Switzerland) · 2026Article
- Relative Localization and Circumnavigation of a UGV0 Based on Mixed Measurements of Multi-UAVs by Employing Intelligent Sensors.Sensors (Basel, Switzerland) · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Visual-inertial odometry (VIO) algorithms, fusing various features such as points and lines, are able to improve their performance in challenging scenes while the running time severely increases. In this paper, we propose a novel lightweight point-line visual-inertial odometry algorithm to solve this problem, called LRPL-VIO. Firstly, a fast line matching method is proposed based on the assumption that the photometric values of endpoints and midpoints are invariant between consecutive frames, which greatly reduces the time consumption of the front end. Then, an efficient filter-based state estimation framework is designed to finish information fusion (point, line, and inertial). Fresh measurements of line features with good tracking quality are selected for state estimation using a unique feature selection scheme, which improves the efficiency of the proposed algorithm. Finally, validation experiments are conducted on public datasets and in real-world tests to evaluate the performance of LRPL-VIO and the results show that we outperform other state-of-the-art algorithms especially in terms of speed and robustness.
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Registered trials
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