Papers Radar odometry
“Radar odometry” 태그가 달린 논문 15편 · 필터 해제
RaDiVe: Robust 4D Radar Odometry with Distance-Bounded NDT and Velocity-Discrepancy Point Uncertainty
Recent advances in 4D radar enable robust perception in adverse weather; however, the inherent sparsity, noise, and limited positional precision of radar point clouds pose significant challenges for registration-based od…
Computational EfficiencyRadar odometryPoint CloudsPushing Radar Odometry Beyond the Pavement: Current Capabilities and Challenges
Radar offers unique advantages for localization in unstructured environments, including robustness to weather, lighting, and airborne particulates. While most prior work has studied radar odometry in urban, largely plana…
Radar odometryRadar Odometry Subject to High Tilt Dynamics of Subarctic Environments
Rotating FMCW radar odometry methods often assume flat ground conditions. While this assumption is sufficient in many scenarios, including urban environments or flat mining setups, the highly dynamic terrain of subarctic…
Radar odometry3DRO: Lidar-level SE(3) Direct Radar Odometry Using a 2D Imaging Radar and a Gyroscope
Recently, the robotics community has regained interest in radar-based perception and state estimation. A 2D imaging radar provides dense 360deg information about the environment. Despite the radar antenna's cone of emiss…
Radar odometryGeometrically-Constrained Radar-Inertial Odometry via Continuous Point-Pose Uncertainty Modeling
Radar odometry is crucial for robust localization in challenging environments; however, the sparsity of reliable returns and distinctive noise characteristics impede its performance. This paper introduces geometrically-c…
Radar odometryEqui-RO: A 4D mmWave Radar Odometry via Equivariant Networks
Autonomous vehicles and robots rely on accurate odometry estimation in GPS-denied environments. While LiDARs and cameras struggle under extreme weather, 4D mmWave radar emerges as a robust alternative with all-weather op…
Autonomous VehiclesRadar odometryDNOI-4DRO: Deep 4D Radar Odometry with Differentiable Neural-Optimization Iterations
A novel learning-optimization-combined 4D radar odometry model, named DNOI-4DRO, is proposed in this paper. The proposed model seamlessly integrates traditional geometric optimization with end-to-end neural network train…
Radar odometryDRO: Doppler-Aware Direct Radar Odometry
A renaissance in radar-based sensing for mobile robotic applications is underway. Compared to cameras or lidars, millimetre-wave radars have the ability to `see' through thin walls, vegetation, and adversarial weather co…
Radar odometryRadarLCD: Learnable Radar-based Loop Closure Detection Pipeline
Loop Closure Detection (LCD) is an essential task in robotics and computer vision, serving as a fundamental component for various applications across diverse domains. These applications encompass object recognition, imag…
Image RetrievalLoop Closure DetectionObject RecognitionRadar odometrySuccessive Pose Estimation and Beam Tracking for mmWave Vehicular Communication Systems
The millimeter wave (mmWave) radar sensing-aided communications in vehicular mobile communication systems is investigated. To alleviate the beam training overhead under high mobility scenarios, a successive pose estimati…
Pose EstimationRadar odometryCFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry
This paper presents the accurate, highly efficient, and learning-free method CFEAR Radarodometry for large-scale radar odometry estimation. By using a filtering technique that keeps the k strongest returns per azimuth an…
CPURadar odometryTranslationMIMO-SAR: A Hierarchical High-resolution Imaging Algorithm for mmWave FMCW Radar in Autonomous Driving
Millimeter-wave radars are being increasingly integrated into commercial vehicles to support advanced driver-assistance system features. A key shortcoming for present-day vehicular radar imaging is poor azimuth resolutio…
Autonomous DrivingRadar odometryMVP: Unified Motion and Visual Self-Supervised Learning for Large-Scale Robotic Navigation
Autonomous navigation emerges from both motion and local visual perception in real-world environments. However, most successful robotic motion estimation methods (e.g. VO, SLAM, SfM) and vision systems (e.g. CNN, visual …
Autonomous DrivingAutonomous NavigationAutonomous VehiclesMotion Estimation+9Under the Radar: Learning to Predict Robust Keypoints for Odometry Estimation and Metric Localisation in Radar
This paper presents a self-supervised framework for learning to detect robust keypoints for odometry estimation and metric localisation in radar. By embedding a differentiable point-based motion estimator inside our arch…
Radar odometryMasking by Moving: Learning Distraction-Free Radar Odometry from Pose Information
This paper presents an end-to-end radar odometry system which delivers robust, real-time pose estimates based on a learned embedding space free of sensing artefacts and distractor objects. The system deploys a fully diff…
Radar odometry