Self-Mixing Laser Interferometry for Robotic Tactile Sensing

TL;DR

This paper introduces a novel robotic fingertip using self-mixing interferometry (SMI) for tactile sensing, demonstrating higher sensitivity and noise resilience compared to acoustic methods, thus advancing robotic slip and contact detection.

Contribution

The first implementation of SMI in robotic fingertips for slip and contact sensing, validated through experiments and compared with acoustic sensing.

Findings

SMI detects microvibrations more sensitively than acoustic sensors.

SMI exhibits greater resilience to ambient noise.

SMI-based tactile sensing shows promise for robotic manipulation.

Abstract

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.