What defines an affordance? The diagnosticity of visual features for the differention of affordances

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Virtual reality for safe testing and development in collaborative robotics: challenges and perspectives

Publication . Bermúdez i Badia, Sergi; Silva, Paula Alexandra; Branco, Diogo; Pinto, Ana; Carvalho, Carla; Menezes, Paulo; Almeida, Jorge; Pilacinski, Artur

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.

2022Journal article

Open access