用毫米波实现家庭机器人无感交互，位置任意都准。
WaveMan: mmWave-Based Room-Scale Human Interaction Perception for Humanoid Robots
- 通过视角对齐与频谱增强，让毫米波感知适应不同位置。
- 自由走动测试准确率从33%提升至94.33%。
- 适合关注隐私保护与泛化能力的机器人交互研究者。
家庭环境中可靠的人机交互（HRI）受限于两个核心需求：对用户任意位置的鲁棒性以及用户隐私保护。毫米波（mmWave）传感天然具备隐私保护特性，是实现室级人机交互的有前途模态。然而，现有基于mmWave的交互感知系统在未见距离或视角下泛化能力差。为此，我们提出WaveMan，一种空间自适应的室级感知系统，可在任意用户位置实现可靠的交互感知。WaveMan结合视角对齐与频谱增强以保持空间一致性，并采用双通道注意力机制实现鲁棒特征提取。五名参与者实验表明，在固定位置评估下，WaveMan以五分之一的训练位置达到与基线相当的跨位置准确率；在随机自由位置测试中，准确率从33.00%提升至94.33%，验证了该方法在无约束用户位置下实现可靠、隐私保护式交互的可行性。
原文摘要 · Abstract (English)
Reliable humanoid-robot interaction (HRI) in household environments is constrained by two fundamental requirements, namely robustness to unconstrained user positions and preservation of user privacy. Millimeter-wave (mmWave) sensing inherently supports privacy-preserving interaction, making it a promising modality for room-scale HRI. However, existing mmWave-based interaction-sensing systems exhibit poor spatial generalization at unseen distances or viewpoints. To address this challenge, we introduce WaveMan, a spatially adaptive room-scale perception system that restores reliable human interaction sensing across arbitrary user positions. WaveMan integrates viewpoint alignment and spectrogram enhancement for spatial consistency, with dual-channel attention for robust feature extraction. Experiments across five participants show that, under fixed-position evaluation, WaveMan achieves the same cross-position accuracy as the baseline with five times fewer training positions. In random free-position testing, accuracy increases from 33.00% to 94.33%, enabled by the proposed method. These results demonstrate the feasibility of reliable, privacy-preserving interaction for household humanoid robots across unconstrained user positions.
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