Virtual Reality for Safe Testing and Development in Collaborative Robotics: Challenges and Perspectives

Author:

Badia Sergi Bermúdez iORCID,Silva Paula Alexandra,Branco DiogoORCID,Pinto AnaORCID,Carvalho Carla,Menezes PauloORCID,Almeida Jorge,Pilacinski ArturORCID

Abstract

Collaborative robots (cobots) could help humans in tasks that are mundane, dangerous or where direct human contact carries risk. Yet, the collaboration between humans and robots is severely limited by the aspects of the safety and comfort of human operators. In this paper, we outline the use of extended reality (XR) as a way to test and develop collaboration with robots. We focus on virtual reality (VR) in simulating collaboration scenarios and the use of cobot digital twins. This is specifically useful in situations that are difficult or even impossible to safely test in real life, such as dangerous scenarios. We describe using XR simulations as a means to evaluate collaboration with robots without putting humans at harm. We show how an XR setting enables combining human behavioral data, subjective self-reports, and biosignals signifying human comfort, stress and cognitive load during collaboration. Several works demonstrate XR can be used to train human operators and provide them with augmented reality (AR) interfaces to enhance their performance with robots. We also provide a first attempt at what could become the basis for a human–robot collaboration testing framework, specifically for designing and testing factors affecting human–robot collaboration. The use of XR has the potential to change the way we design and test cobots, and train cobot operators, in a range of applications: from industry, through healthcare, to space operations.

Funder

University of Coimbra

Fundação para a Ciência e Tecnologia

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference78 articles.

1. E-Leadership and Teleworking in Times of COVID-19 and Beyond: What We Know and Where Do We Go

2. Robots and risk of COVID-19 workplace contagion: Evidence from Italy

3. How Robots Became Essential Workers in the COVID-19 Response https://spectrum.ieee.org/how-robots-became-essential-workers-in-the-covid19-response

4. IFR Position Paper Demystifying Collaborative Industrial Robots,2018

5. Keep The Robot In The Cage—How Effective (And Safe) Are Co-Bots? https://www.forbes.com/sites/charlestowersclark/2019/09/11/keep-the-robot-in-the-cagehow-effective--safe-are-co-bots/

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