Audio-based Roughness Sensing and Tactile Feedback for Haptic Perception in Telepresence

TL;DR

This paper presents a low-cost, real-time audio-based system for sensing surface roughness and providing tactile feedback to enhance haptic perception in teleoperation, validated through experiments and a competition win.

Contribution

It introduces a novel audio-based sensing and feedback system for surface roughness detection in telepresence robots, with real-time processing and publicly available datasets.

Findings

High temporal resolution and low latency roughness estimates

Effective tactile feedback improves user perception

System successfully used in competition for manipulation tasks

Abstract

Haptic perception is highly important for immersive teleoperation of robots, especially for accomplishing manipulation tasks. We propose a low-cost haptic sensing and rendering system, which is capable of detecting and displaying surface roughness. As the robot fingertip moves across a surface of interest, two microphones capture sound coupled directly through the fingertip and through the air, respectively. A learning-based detector system analyzes the data in real time and gives roughness estimates with both high temporal resolution and low latency. Finally, an audio-based vibrational actuator displays the result to the human operator. We demonstrate the effectiveness of our system through lab experiments and our winning entry in the ANA Avatar XPRIZE competition finals, where briefly trained judges solved a roughness-based selection task even without additional vision feedback. We publish our dataset used for training and evaluation together with our trained models to enable reproducibility of results.