This article presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry
framework. Building on a highly efficient tightly coupled iterated Kalman filter, FAST-LIO2 …

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 introduce M2DGR: a novel large-scale dataset collected by a ground robot with a full
sensor-suite including six fish-eye and one sky-pointing RGB cameras, an infrared camera …

Factor graph optimization (FGO) recently has attracted attention as an alternative to the
extended Kalman filter (EKF) for GNSS-INS integration. This study evaluates both loosely …

We present a novel tightly-coupled LiDAR-inertial odometry and mapping scheme for both
solid-state and mechanical LiDARs. As frontend, a feature-based lightweight LiDAR …

Multi-modal data fusion has gained popularity due to its diverse applications, leading to an
increased demand for external sensor calibration. Despite several proven calibration …

Autonomous vehicles integrate complex software stacks for realizing the necessary iterative
perception, planning, and action operations. One of the foundational layers of such stacks is …

Multi-modal fusion is a fundamental task for the perception of an autonomous driving
system, which has recently intrigued many researchers. However, achieving a rather good …

With the continuous maturation and application of autonomous driving technology, a
systematic examination of open-source autonomous driving datasets becomes instrumental …

Accurate positioning in urban canyons remains a challenging problem. To facilitate the
research and development of reliable and precise positioning methods using multiple …