Boreas: A multi-season autonomous driving dataset
The Boreas dataset was collected by driving a repeated route over the course of 1 year,
resulting in stark seasonal variations and adverse weather conditions such as rain and …
resulting in stark seasonal variations and adverse weather conditions such as rain and …
Deep learning-based robust positioning for all-weather autonomous driving
Interest in autonomous vehicles (AVs) is growing at a rapid pace due to increased
convenience, safety benefits and potential environmental gains. Although several leading …
convenience, safety benefits and potential environmental gains. Although several leading …
Sensors and sensor fusion methodologies for indoor odometry: A review
Although Global Navigation Satellite Systems (GNSSs) generally provide adequate
accuracy for outdoor localization, this is not the case for indoor environments, due to signal …
accuracy for outdoor localization, this is not the case for indoor environments, due to signal …
Are we ready for radar to replace lidar in all-weather mapping and localization?
We present an extensive comparison between three topometric localization systems: radar-
only, lidar-only, and a cross-modal radar-to-lidar system across varying seasonal and …
only, lidar-only, and a cross-modal radar-to-lidar system across varying seasonal and …
A new wave in robotics: Survey on recent mmwave radar applications in robotics
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 …
a focus on unique capabilities, and discuss future opportunities based on the state of the art …
4dradarslam: A 4d imaging radar slam system for large-scale environments based on pose graph optimization
LiDAR-based SLAM may easily fail in adverse weathers (eg, rain, snow, smoke, fog), while
mmWave Radar remains unaffected. However, current researches are primarily focused on …
mmWave Radar remains unaffected. However, current researches are primarily focused on …
Lidar-level localization with radar? the cfear approach to accurate, fast, and robust large-scale radar odometry in diverse environments
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 …
odometry estimation using spinning radar, empirically found to generalize well across very …
4d radar-based pose graph slam with ego-velocity pre-integration factor
4D imaging radars (4D radars) provide point clouds with range, azimuth, elevation as well
as Doppler velocity. They are much cheaper sensors than LiDARs and can operate under …
as Doppler velocity. They are much cheaper sensors than LiDARs and can operate under …
Cfear radarodometry-conservative filtering for efficient and accurate radar odometry
This paper presents an accurate, highly efficient and learning free method for large-scale
radar odometry estimation. By using a simple filtering technique that keeps the strongest …
radar odometry estimation. By using a simple filtering technique that keeps the strongest …
Radar odometry for autonomous ground vehicles: A survey of methods and datasets
NJ Abu-Alrub, NA Rawashdeh - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Radar odometry has been gaining attention in the last decade. It stands as one of the best
solutions for robotic state estimation in unfavorable conditions; conditions where other …
solutions for robotic state estimation in unfavorable conditions; conditions where other …