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 …

High-dimensional nonlinear state estimation is at the heart of inertial-aided navigation
systems (INS). Traditional methods usually rely on good initialization and find difficulty in …

We present LINS, a lightweight lidar-inertial state estimator, for real-time ego-motion
estimation. The proposed method enables robust and efficient navigation for ground …

Legged robots require knowledge of pose and velocity in order to maintain stability and
execute walking paths. Current solutions either rely on vision data, which is susceptible to …

This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-
camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual …

Human pose estimation provides valuable information for biomedical research on human
movement and applications, such as entertainment and physical exercise. The fusion of …

Visual navigation systems are susceptible to complex environments, while inertial
navigation systems (INS) are not affected by external factors. Hence, we present IC-GVINS …

Nowadays, high-precision navigation is a fundamental prerequisite for autonomous driving
technology. However, it is often difficult for a stand-alone sensor to meet the needs of high …

This paper introduces a robot system that is designed to assist postal workers by carrying
heavy packages in a complex urban environment such as apartment complex. Since most of …