Autonomous driving vehicles require both a precise localization and map** solution in
different driving environment. In this context, Simultaneous Localization and Map** …

As inertial and visual sensors are becoming ubiquitous, visual-inertial navigation systems
(VINS) have prevailed in a wide range of applications from mobile augmented reality to …

In this paper, we present an open platform, termed OpenVINS, for visual-inertial estimation
research for both the academic community and practitioners from industry. The open …

Simultaneous Localization and Map** is now widely adopted by many applications, and
researchers have produced very dense literature on this topic. With the advent of smart …

Light-weight time-of-flight (ToF) depth sensors are compact and cost-efficient, and thus
widely used on mobile devices for tasks such as autofocus and obstacle detection. However …

Although VSLAM/VISLAM has achieved great success, it is still difficult to quantitatively
evaluate the localization results of different kinds of SLAM systems from the aspect of …

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

Most previous learning-based visual odometry (VO) methods take VO as a pure tracking
problem. In contrast, we present a VO framework by incorporating two additional …