The ability of intelligent unmanned platforms to achieve autonomous navigation and
positioning in a large-scale environment has become increasingly demanding, in which …

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 …

This letter presents a computationally efficient and robust LiDAR-inertial odometry
framework. We fuse LiDAR feature points with IMU data using a tightly-coupled iterated …

This letter presents an incremental voxel-based lidar-inertial odometry (LIO) method for fast-
tracking spinning and solid-state lidar scans. To achieve the high tracking speed, we neither …

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 …

OpenStreetMap (OSM) is widely used in outdoor navigation research recently, which is
publicly available and can provide a wide range of road information for outdoor robot …

A local Bundle Adjustment (BA) on a sliding window of keyframes has been widely used in
visual SLAM and proved to be very effective in lowering the drift. But in lidar SLAM, BA …

We present SLOPER4D, a novel scene-aware dataset collected in large urban
environments to facilitate the research of global human pose estimation (GHPE) with human …

We present an efficient multi-sensor odometry system for mobile platforms that jointly
optimizes visual, lidar, and inertial information within a single integrated factor graph. This …

Multi-sensor fusion of multi-modal measurements from commodity inertial, visual and LiDAR
sensors to provide robust and accurate 6DOF pose estimation holds great potential in …