用自混合激光干涉技术实现机器人指尖无接触触觉感知。
Self-Mixing Laser Interferometry for Robotic Tactile Sensing
- 用自混合激光干涉检测微振动，无需接触物体。
- 对微滑动敏感，抗环境噪声能力强于声学传感。
- 适合需要高灵敏度触觉的机器人操作场景。
自混合激光干涉（SMI）以高灵敏度检测微振动著称，且无需与目标物理接触。在机器人领域，微振动传统上被用作物体滑移的标志，最近也被视为外部接触的显著指标。本文首次提出基于SMI的机器人指尖，用于滑移和外部接触感知。通过对比封装前后受控振动源的测量结果验证了设计有效性，并在四项实验中将SMI与声学传感进行比较。结果归纳为技术决策图：SMI对细微滑移更敏感，且显著更耐环境噪声。结论表明，将SMI集成至机器人指尖为触觉感知开辟了新路径。设计与数据文件已公开于https://github.com/RemkoPr/icra2025-SMI-tactile-sensing。
原文摘要 · Abstract (English)
Self-mixing interferometry (SMI) has been lauded for its sensitivity in detecting microvibrations, while requiring no physical contact with its target. In robotics, microvibrations have traditionally been interpreted as a marker for object slip, and recently as a salient indicator of extrinsic contact. We present the first-ever robotic fingertip making use of SMI for slip and extrinsic contact sensing. The design is validated through measurement of controlled vibration sources, both before and after encasing the readout circuit in its fingertip package. Then, the SMI fingertip is compared to acoustic sensing through four experiments. The results are distilled into a technology decision map. SMI was found to be more sensitive to subtle slip events and significantly more resilient against ambient noise. We conclude that the integration of SMI in robotic fingertips offers a new, promising branch of tactile sensing in robotics. Design and data files are available at https://github.com/RemkoPr/icra2025-SMI-tactile-sensing.
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