A Biomimetic Fingerprint for Robotic Tactile Sensing

TL;DR

This paper introduces a 3D-printed fingerprint pattern for robotic tactile sensors that significantly enhances vibration signals, improving dynamic tactile feedback on robotic hands.

Contribution

The authors designed and tested a biomimetic fingerprint pattern that boosts vibration signal strength, addressing robustness and surface adaptability issues in tactile sensors.

Findings

Fingerprint pattern increased vibration signal power over 11 times.

Created a public dataset with 52 objects of various materials.

Demonstrated improved tactile feedback on a robotic hand.

Abstract

Tactile sensors have been developed since the early '70s and have greatly improved, but there are still no widely adopted solutions. Various technologies, such as capacitive, piezoelectric, piezoresistive, optical, and magnetic, are used in haptic sensing. However, most sensors are not mechanically robust for many applications and cannot cope well with curved or sizeable surfaces. Aiming to address this problem, we present a 3D-printed fingerprint pattern to enhance the body-borne vibration signal for dynamic tactile feedback. The 3D-printed fingerprint patterns were designed and tested for an RH8D Adult size Robot Hand. The patterns significantly increased the signal's power to over 11 times the baseline. A public haptic dataset including 52 objects of several materials was created using the best fingerprint pattern and material.