用毫米波雷达实现机器人倒液时的高精度液位实时追踪
RadarEye: Robust Liquid Level Tracking Using mmWave Radar in Robotic Pouring
- 通过高分辨率波束成形与物理约束追踪算法，提升雷达对液面的感知能力
- 实测液位误差中位数仅0.35厘米，更新频率达每毫秒0.62次
- 在光线变化和液体反光场景下优于视觉与超声方案，适合工业倒液任务
透明液体在机器人倒液过程中对感知系统构成挑战：镜面反射与折射效应及光照变化会削弱视觉线索，导致液位估计不可靠。为解决此问题，本文提出RadarEye，一种用于整个倒液过程的实时毫米波雷达信号处理流水线，实现鲁棒的液位估计与跟踪。该系统集成（i）高分辨率距离-角度波束成形模块以感知液面，（ii）物理信息驱动的中途追踪器，有效抑制多路径干扰，保持对液面锁定，即使在液流杂波和容器反射干扰下仍稳定工作。系统延迟低于1毫秒。在真实机器人水倒实验中，RadarEye实现0.35厘米的中位绝对高度误差，每帧更新耗时0.62毫秒，显著优于视觉与超声基线。
原文摘要 · Abstract (English)
Transparent liquid manipulation in robotic pouring remains challenging for perception systems: specular/refraction effects and lighting variability degrade visual cues, undermining reliable level estimation. To address this challenge, we introduce RadarEye, a real-time mmWave radar signal processing pipeline for robust liquid level estimation and tracking during the whole pouring process. RadarEye integrates (i) a high-resolution range-angle beamforming module for liquid level sensing and (ii) a physics-informed mid-pour tracker that suppresses multipath to maintain lock on the liquid surface despite stream-induced clutter and source container reflections. The pipeline delivers sub-millisecond latency. In real-robot water-pouring experiments, RadarEye achieves a 0.35 cm median absolute height error at 0.62 ms per update, substantially outperforming vision and ultrasound baselines.
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