用振动信号实现低成本高精度机器人触觉定位与轨迹追踪
Vibro-Sense: Robust Vibration-based Impulse Response Localization and Trajectory Tracking for Robotic Hands
- 用7个低成本麦克风捕捉接触振动，通过音频时频变换模型解码
- 静态定位误差低于5毫米，动态下仍能稳定追踪运动轨迹
- 适合对触觉感知成本敏感的机器人研究者，开源数据模型可用
丰富的接触感知对机器人操作至关重要，但传统触觉皮肤成本高、集成复杂。本文提出一种可扩展的替代方案：通过振动声学传感实现全身高精度触觉定位。在机械手上部署7个低成本压电麦克风，结合音频谱图变压器，解码物理交互产生的振动特征。在静态与动态任务中广泛测试表明，静态条件下定位误差低于5毫米。分析显示材料属性影响显著：刚性材料（如金属）因响应尖锐、带宽高，利于冲击响应定位；纹理材料（如木头）则提供更优的摩擦特征，适用于轨迹追踪。系统在机器人自身运动下仍保持鲁棒性，有效追踪。核心贡献在于证明复杂接触动力学可从简单振动信号中有效解码，为机器人接触感知提供了可行、廉价的新路径。为加速研究，我们公开全部数据集、模型与实验配置。
原文摘要 · Abstract (English)
Rich contact perception is crucial for robotic manipulation, yet traditional tactile skins remain expensive and complex to integrate. This paper presents a scalable alternative: high-accuracy whole-body touch localization via vibro-acoustic sensing. By equipping a robotic hand with seven low-cost piezoelectric microphones and leveraging an Audio Spectrogram Transformer, we decode the vibrational signatures generated during physical interaction. Extensive evaluation across stationary and dynamic tasks reveals a localization error of under 5 mm in static conditions. Furthermore, our analysis highlights the distinct influence of material properties: stiff materials (e.g., metal) excel in impulse response localization due to sharp, high-bandwidth responses, whereas textured materials (e.g., wood) provide superior friction-based features for trajectory tracking. The system demonstrates robustness to the robot's own motion, maintaining effective tracking even during active operation. Our primary contribution is demonstrating that complex physical contact dynamics can be effectively decoded from simple vibrational signals, offering a viable pathway to widespread, affordable contact perception in robotics. To accelerate research, we provide our full datasets, models, and experimental setups as open-source resources.
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