# Tactile Model O: Fabrication and testing of a 3d-printed, three-fingered tactile robot hand

## TL;DR

This paper introduces the Tactile Model O, a 3D-printed, three-fingered robotic hand equipped with tactile sensors and machine vision, demonstrating effective grasping and object classification capabilities for robotic research.

## Contribution

The paper presents a novel tactile robot hand design integrating biomimetic sensors and vision systems, enabling advanced tactile sensing and grasping evaluation.

## Key findings

- Achieved state-of-the-art tactile object classification accuracy.
- Demonstrated effective grasping performance on YCB objects.
- Validated the platform as a versatile tool for robot hand research.

## Abstract

Bringing tactile sensation to robotic hands will allow for more effective grasping, along with the wide range of benefits of human-like touch. Here we present a 3D-printed, three-fingered tactile robot hand comprising an OpenHand Model O customized to house a TacTip soft biomimetic tactile sensor in the distal phalanx of each finger. We expect that combining the grasping capabilities of this underactuated hand with sophisticated tactile sensing will result in an effective platform for robot hand research -- the Tactile Model O (T-MO). The design uses three JeVois machine vision systems, each comprising a miniature camera in the tactile fingertip with a processing module in the base of the hand. To evaluate the capabilities of the T-MO, we benchmark its grasping performance using the Gripper Assessment Benchmark on the YCB object set. Tactile sensing capabilities are evaluated by performing tactile object classification on 26 objects and predicting whether a grasp will successfully lift each object. Results are consistent with the state of the art, taking advantage of advances in deep learning applied to tactile image outputs. Overall, this work demonstrates that the T-MO is an effective platform for robot hand research and we expect it to open-up a range of applications in autonomous object handling. Supplemental video: https://youtu.be/RTcCpgffCrQ.