Visual-inertial simultaneous localization and mapping (VI-SLAM) is popular research topic in
robotics. Because of its advantages in terms of robustness, VI-SLAM enjoys wide …

Virtual reality, augmented reality, robotics, and autonomous driving, have recently attracted
much attention from both academic and industrial communities, in which image-based …

Traditional approaches to stereo visual simultaneous localization and mapping (SLAM) rely
on point features to estimate the camera trajectory and build a map of the environment. In …

To address the problem of estimating camera trajectory and to build a structural three-
dimensional (3D) map based on inertial measurements and visual observations, this paper …

In feature-based simultaneous localization and mapping (SLAM), line features complement
the sparsity of point features, making it possible to map the surrounding environment …

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 …

In this paper, we develop a robust efficient visual SLAM system that utilizes heterogeneous
point and line features. By leveraging ORB-SLAM [1], the proposed system consists of stereo …

This paper presents a new implementation method for efficient simultaneous localization
and mapping using a forward-viewing monocular vision sensor. The method is developed to …

Manhattan and Atlanta worlds hold for the structured scenes with only vertical and horizontal
dominant directions (DDs). To describe the scenes with additional sloping DDs, a mixture of …

This paper presents a visual SLAM system that uses both points and lines for robust camera
localization, and simultaneously performs a piece-wise planar reconstruction (PPR) of the …