PyTouch: A Machine Learning Library for Touch Processing

TL;DR

PyTouch is an open-source machine learning library designed for processing tactile sensor data, enabling improved touch detection, slip, and object pose estimation for robotics and tactile sensing applications.

Contribution

It introduces the first dedicated ML library for touch signal processing, offering modular, scalable, and validated tools for the tactile sensing community.

Findings

Effective touch detection and slip estimation demonstrated

High accuracy in object pose estimation

Library validated on real-world tactile sensor data

Abstract

With the increased availability of rich tactile sensors, there is an equally proportional need for open-source and integrated software capable of efficiently and effectively processing raw touch measurements into high-level signals that can be used for control and decision-making. In this paper, we present PyTouch -- the first machine learning library dedicated to the processing of touch sensing signals. PyTouch, is designed to be modular, easy-to-use and provides state-of-the-art touch processing capabilities as a service with the goal of unifying the tactile sensing community by providing a library for building scalable, proven, and performance-validated modules over which applications and research can be built upon. We evaluate PyTouch on real-world data from several tactile sensors on touch processing tasks such as touch detection, slip and object pose estimations. PyTouch is open-sourced at https://github.com/facebookresearch/pytouch .