Odometry is crucial for robot navigation, particularly in situations where global positioning
methods like global positioning system are unavailable. The main goal of odometry is to …

There is a current increase in the development of" 4D" Doppler-capable radar and lidar
range sensors that produce 3D point clouds where all points also have information about the …

Spinning, frequency-modulated continuous-wave (FMCW) radars with 360° coverage have
been gaining popularity for autonomous-vehicle navigation. However, unlike …

Accurate and robust vehicle localization in highly urbanized areas is challenging. Sensors
are often corrupted in those complicated and large-scale environments. This article …

We present a novel 3D odometry method that recovers the full motion of a vehicle only from
a Doppler-capable range sensor. It leverages the radial velocities measured from the scene …

In contrast to traditional 3D LiDAR, the newly introduced 4D LiDAR not only provides
conventional point cloud data but also offers Doppler velocity measurements of the point …

Conventional LiDAR-inertial odometry (LIO) or SLAM methods heavily rely on geometric
features of environments, as LiDARs primarily provide range measurements instead of …

Robust initialization is crucial for online systems. In the letter, a high-frequency and resilient
initialization framework is designed for LiDAR-inertial systems, leveraging both inertial …