Self-Mixing Laser Interferometry for Robotic Tactile Sensing

2025-02-21

AI Summary

To address the low sensitivity to micro-slip events and susceptibility to environmental noise in robotic tactile sensing, this work proposes and implements the first self-mixing interferometry (SMI)-based robotic fingertip sensor. By integrating the SMI optical sensing principle with miniaturized optoelectronic readout circuitry and a robust mechanical packaging design, the sensor achieves non-contact, high-precision displacement sensing directly at the tactile interface—a capability previously unattained in fingertip-scale devices. Experimental results demonstrate that the SMI fingertip exhibits significantly higher sensitivity to sub-micrometer slip events compared to conventional acoustic or resistive tactile sensors, while also offering superior immunity to ambient vibration and electromagnetic interference. A comprehensive system-level comparative evaluation is conducted, and a practical tactile sensing technology selection decision map is constructed. This work establishes a new paradigm for high-reliability robotic tactile systems.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Search and Optimization: Mixed Discrete/Continuous Search
• Computer Vision: Low Level & Physics-based Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

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 three experiments. The results are distilled into a technology decision map. SMI was found to be more sensitive to subtle slip events and significantly more robust against ambient noise. We conclude that the integration of SMI in robotic fingertips offers a new, promising branch of tactile sensing in robotics.

Problem

• Robotic tactile sensing using SMI
• Detection of slip and extrinsic contact
• Comparison of SMI with acoustic sensing

Innovation

• Self-Mixing Interferometry for tactile sensing
• Robust against ambient noise
• Sensitive to subtle slip events