3D Cal: An Open-Source Software Library for Calibrating Tactile Sensors

TL;DR

3D Cal is an open-source library that automates tactile sensor calibration using a 3D printer as a probing device, enabling efficient data collection and improved depth map reconstruction for robotic tactile sensing.

Contribution

It introduces a novel, automated calibration method for vision-based tactile sensors using a low-cost 3D printer, reducing manual effort and enhancing calibration accuracy.

Findings

Successfully calibrated DIGIT and GelSight Mini sensors with high-quality depth maps

Provided practical data collection guidelines for these sensors

Demonstrated good generalization on unseen objects

Abstract

Tactile sensing plays a key role in enabling dexterous and reliable robotic manipulation, but realizing this capability requires substantial calibration to convert raw sensor readings into physically meaningful quantities. Despite its near-universal necessity, the calibration process remains ad hoc and labor-intensive. Here, we introduce 3D Cal, an open-source library that transforms a low-cost 3D printer into an automated probing device capable of generating large volumes of labeled training data for tactile sensor calibration. We demonstrate the utility of 3D Cal by calibrating two commercially available vision-based tactile sensors, DIGIT and GelSight Mini, to reconstruct high-quality depth maps using the collected data and a custom convolutional neural network. In addition, we perform a data ablation study to determine how much data is needed for accurate calibration, providing practical guidelines for researchers working with these specific sensors, and we benchmark the trained models on previously unseen objects to evaluate calibration accuracy and generalization performance. By automating tactile sensor calibration, 3D Cal can accelerate tactile sensing research, simplify sensor deployment, and promote the practical integration of tactile sensing in robotic platforms.