POW4R: POint-Wise Full-Velocity Estimation Using 4D Radar-Camera Fusion Beyond Radial Limitations

IF 5.3 2区计算机科学 Q2 ROBOTICS

IEEE Robotics and Automation Letters Pub Date : 2025-09-04 DOI:10.1109/LRA.2025.3606356

Hyun-Yong Jeon;Minseong Choi;Yeongseok Lee;Sangyoon Oh;Seunghoon Yang;Keun Ha Choi;Kyung-Soo Kim

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引用次数: 0

Abstract

This letter proposes an algorithm for full-velocity estimation by fusing radial velocity vectors obtained from 4D radar with optical flow vectors extracted from camera images. The full-velocity algorithm consists of a preprocessing step and a full-velocity vector estimation step. In preprocessing, radar noise is removed and ego-vehicle velocity estimation is enhanced using a Hampel filter for improved robustness in dynamic environments. In the full-velocity estimation stage, the algorithm estimates full-velocity vectors using a formulation derived from mathematical equations that incorporate multiple constraints. To evaluate the proposed method, an embedded system is implemented on a real vehicle, and datasets are collected under various scenarios. Experimental results show that the proposed algorithm significantly improves object velocity estimation performance. (error rate: baseline 81%

$\rightarrow$

proposed 31%).

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POW4R：点明智的全速估计使用四维雷达-相机融合超越径向限制

本文提出了一种将四维雷达获得的径向速度矢量与从相机图像中提取的光流矢量融合的全速度估计算法。该算法包括一个预处理步骤和一个全速矢量估计步骤。在预处理中，去除雷达噪声，并使用Hampel滤波器增强自车速度估计，以提高动态环境下的鲁棒性。在全速估计阶段，该算法使用包含多个约束的数学方程推导出的公式来估计全速矢量。为了评估所提出的方法，在真实车辆上实现了嵌入式系统，并收集了各种场景下的数据集。实验结果表明，该算法显著提高了目标速度估计性能。（错误率：基线81% $\右箭头$建议31%）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Robotics and Automation Letters Computer Science-Computer Science Applications

CiteScore

9.60

自引率

15.40%

发文量

1428

期刊介绍： The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.