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

This article presents an accurate, highly efficient, and learning-free method for large-scale
odometry estimation using spinning radar, empirically found to generalize well across very …

Sensing technology plays a crucial role in bridging the physical and digital worlds. By
transforming a multitude of physical phenomena into digital data, it significantly enhances …

Recently, several 4D radar datasets have been published due to its high resolution and
robustness in extreme weather conditions. However, most of the recent 4D radar dataset …

Estimation of indoor location is a key capability for indoor location-based services. Among
various solutions, single-chip low-cost millimeter-wave (mmWave) radar as an emerging …

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

Radar sensors are emerging as solutions for perceiving surroundings and estimating ego-
motion in extreme weather conditions. Unfortunately, radar measurements are noisy and …

The problem of estimating the 3D ego-motion velocity using multi-channel FMCW radar
sensors has been studied. For the first time, the problem of ego-motion estimation is treated …

State estimation is a crucial component for the successful implementation of robotic systems,
relying on sensors such as cameras, LiDAR, and IMUs. However, in real-world scenarios …

Consistent motion estimation is fundamental for all mobile autonomous systems. While this
sounds like an easy task, often, it is not the case because of changing environmental …