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Bibliographic Details
Main Authors: Proesmans, Remko, Lips, Thomas, wyffels, Francis
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2504.13711
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author Proesmans, Remko
Lips, Thomas
wyffels, Francis
author_facet Proesmans, Remko
Lips, Thomas
wyffels, Francis
contents Self-mixing interferometry (SMI) has been lauded for its sensitivity in detecting microvibrations, while requiring no physical contact with its target. Microvibrations, i.e., sounds, have recently been used as a salient indicator of extrinsic contact in robotic manipulation. In previous work, we presented a robotic fingertip using SMI for extrinsic contact sensing as an ambient-noise-resilient alternative to acoustic sensing. Here, we extend the validation experiments to the frequency domain. We find that for broadband ambient noise, SMI still outperforms acoustic sensing, but the difference is less pronounced than in time-domain analyses. For targeted noise disturbances, analogous to multiple robots simultaneously collecting data for the same task, SMI is still the clear winner. Lastly, we show how motor noise affects SMI sensing more so than acoustic sensing, and that a higher SMI readout frequency is important for future work. Design and data files are available at https://github.com/RemkoPr/icra2025-SMI-tactile-sensing.
format Preprint
id arxiv_https___arxiv_org_abs_2504_13711
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Self-Mixing Laser Interferometry: In Search of an Ambient Noise-Resilient Alternative to Acoustic Sensing
Proesmans, Remko
Lips, Thomas
wyffels, Francis
Robotics
Self-mixing interferometry (SMI) has been lauded for its sensitivity in detecting microvibrations, while requiring no physical contact with its target. Microvibrations, i.e., sounds, have recently been used as a salient indicator of extrinsic contact in robotic manipulation. In previous work, we presented a robotic fingertip using SMI for extrinsic contact sensing as an ambient-noise-resilient alternative to acoustic sensing. Here, we extend the validation experiments to the frequency domain. We find that for broadband ambient noise, SMI still outperforms acoustic sensing, but the difference is less pronounced than in time-domain analyses. For targeted noise disturbances, analogous to multiple robots simultaneously collecting data for the same task, SMI is still the clear winner. Lastly, we show how motor noise affects SMI sensing more so than acoustic sensing, and that a higher SMI readout frequency is important for future work. Design and data files are available at https://github.com/RemkoPr/icra2025-SMI-tactile-sensing.
title Self-Mixing Laser Interferometry: In Search of an Ambient Noise-Resilient Alternative to Acoustic Sensing
topic Robotics
url https://arxiv.org/abs/2504.13711