Developing whole-body tactile skins for robots remains a challenging task, as existing solutions often prioritize modular, one-size-fits-all designs, which, while versatile, fail to account for the robot's specific shape and the unique demands of its operational context. In this work, we introduce GenTact Toolbox, a computational pipeline for creating versatile whole-body tactile skins tailored to both robot shape and application domain. Our method includes procedural mesh generation for conforming to a robot's topology, task-driven simulation to refine sensor distribution, and multi-material 3D printing for shape-agnostic fabrication. We validate our approach by creating and deploying six capacitive sensing skins on a Franka Research 3 robot arm in a human-robot interaction scenario. This work represents a shift from "one-size-fits-all" tactile sensors toward context-driven, highly adaptable designs that can be customized for a wide range of robotic systems and applications. The project website is available at https://hiro-group.ronc.one/gentacttoolbox
@article{arxiv.2412.00711,
title = {GenTact Toolbox: A Computational Design Pipeline to Procedurally Generate Context-Driven 3D Printed Whole-Body Artificial Skins},
author = {Carson Kohlbrenner and Caleb Escobedo and S. Sandra Bae and Alexander Dickhans and Alessandro Roncone},
journal= {arXiv preprint arXiv:2412.00711},
year = {2026}
}
Comments
Camera ready accepted at the IEEE International Conference on Robotics and Automation (ICRA) 2025