TacFinRay: Soft Tactile Fin-Ray Finger with Indirect Tactile Sensing for Robust Grasping

TL;DR

This paper introduces a soft tactile Fin-Ray finger with indirect sensing via an internal camera and neural network, enabling accurate contact detection and robust grasping in soft robotics.

Contribution

It presents a novel biomimetic tactile sensor design that combines indirect sensing with optimized deformation transfer, improving grasping accuracy and robustness.

Findings

Achieved 0.1 mm depth and 2 mm location sensing accuracy.

Demonstrated robust generalization to various indenter shapes.

Significantly improved pick-and-place task performance.

Abstract

We present a tactile-sensorized Fin-Ray finger that enables simultaneous detection of contact location and indentation depth through an indirect sensing approach. A hinge mechanism is integrated between the soft Fin-Ray structure and a rigid sensing module, allowing deformation and translation information to be transferred to a bottom crossbeam upon which are an array of marker-tipped pins based on the biomimetic structure of the TacTip vision-based tactile sensor. Deformation patterns captured by an internal camera are processed using a convolutional neural network to infer contact conditions without directly sensing the finger surface. The finger design was optimized by varying pin configurations and hinge orientations, achieving 0.1\,mm depth and 2mm location-sensing accuracies. The perception demonstrated robust generalization to various indenter shapes and sizes, which was applied to a pick-and-place task under uncertain picking positions, where the tactile feedback significantly improved placement accuracy. Overall, this work provides a lightweight, flexible, and scalable tactile sensing solution suitable for soft robotic structures where the sensing needs situating away from the contact interface.