Robot training with human emotional reactions by means of immersive virtual and augmented reality

Ensuring safety and efficiency in human-robot interactions (HRI) is a challenging and emerging research area, essential to the future success of Robotic Autonomous Systems (RAS). The aim of this PhD is to ensure reliable and safe collaborative HRI for increased productivity and efficiency of RAS in future industrial applications. Humans are capable to interpret emotions, adapt and react to various cues, making co-working with others natural and trustworthy. Industrial robots can't intrinsically do this (e.g. how to pass a tool to a human in a speed and orientation that is perceived safe), therefore coupled with a high payload they may behave in a manner perceived dangerous or threatening, causing anxiety and lack of trust from the human.

This PhD exploits novel Immersive Virtual and Augmented Reality (IVAR) environments to assess and improve the suitability HRI in untested and potentially risky manufacturing tasks. The interdisciplinary research will leverage on low-cost IVAR environment, wearable hardware where virtual experiments will be designed to understand human responses in realistic industrial scenarios.