We survey the current state of millimeterwave (mmWave) radar applications in robotics with
a focus on unique capabilities, and discuss future opportunities based on the state of the art …

Millimeter wave radar can measure distances, directions, and Doppler velocity for objects in
harsh conditions such as fog. The 4D imaging radar with both vertical and horizontal data …

Achieving general 3D motion estimation for all-visibility has been a key challenge in
robotics, especially in extreme environments. The widely adopted camera and LiDAR-based …

Due to the robustness in sensing, radar has been highlighted, overcoming harsh weather
conditions such as fog and heavy snow. In this paper, we present a novel radar-only place …

Simultaneously localization and mapping (SLAM) has been widely used in autonomous
mobile systems to fulfill autonomous navigation. Relocalization plays an important role in …

We present a method for unsupervised learning of single-scan radar embeddings from
sequences of radar images that is suitable for solving the place recognition problem with …

This paper provides an in-depth review of deep learning techniques to address the
challenges of odometry and global ego-localization using frequency modulated continuous …

As an important technology in 3D vision, point-cloud registration has broad development
prospects in the fields of space-based remote sensing, photogrammetry, robotics, and so on …

Automotive mmWave radar has been widely used in the automotive industry due to its small
size, low cost, and complementary advantages to optical sensors (eg, cameras, LiDAR, etc.) …

There is a growing academic interest as well as commercial exploitation of millimetre-wave
scanning radar for autonomous vehicle localisation and scene understanding. Although …