Leveraging line features to improve localization accuracy of point-based visual-inertial
SLAM (VINS) is gaining interest as they provide additional constraints on scene structure …

This letter presents a real-time monocular visual-inertial simultaneous localization and
mapping with point-line fusion and parallel-line fusion. The corner and line features provide …

This paper introduces an efficient direct visual odometry (VO) algorithm using points and
lines. Pixels on lines are generally adopted in direct methods. However, the original …

Visual Simultaneous Localization and Mapping (VSLAM), which serves as the primary
technique for locating autonomous vehicles, has gained tremendous development over the …

State-of-the-art monocular visual-inertial odometry (VIO) approaches rely on sparse point
features in part due to their efficiency, robustness, and prevalence, while ignoring high-level …

In this letter, we present a direct visual odometry (VO) using points and lines. Direct methods
generally choose pixels with sufficient gradients to minimize the photometric error for the …

We propose a novel visual-inertial odometry (VIO) initialization method, which decouples
rotation and translation estimation, and achieves higher efficiency and better robustness …

This letter proposes a novel SLAM framework for stereo and visual inertial odometry
estimation. It builds an efficient and robust parametrization of co-planar points and lines …

In indoor low-texture environments, the point feature-based visual SLAM system has poor
robustness and low trajectory accuracy. Therefore, we propose a visual inertial SLAM …

Visual–inertial odometry (VIO) is widely studied and used in autonomous robots. This article
proposes a novel tightly coupled monocular VIO system based on point-line constraints …