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Enhancing Perceived Safety in Human–Robot Collaborative Construction Using Immersive Virtual Environments

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Abstract

Advances in robotics now permit humans to work collaboratively with robots. However, humans often feel unsafe working alongside robots. Our knowledge of how to help humans overcome this issue is limited by two challenges. One, it is difficult, expensive and time-consuming to prototype robots and set up various work situations needed to conduct studies in this area. Two, we lack strong theoretical models to predict and explain perceived safety and its influence on human–robot work collaboration (HRWC). To address these issues, we introduce the Robot Acceptance Safety Model (RASM) and employ immersive virtual environments (IVEs) to examine perceived safety of working on tasks alongside a robot. Results from a between-subjects experiment done in an IVE show that separation of work areas between robots and humans increases perceived safety by promoting team identification and trust in the robot. In addition, the more participants felt it was safe to work with the robot, the more willing they were to work alongside the robot in the future.

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hal-02895952 , version 1 (10-07-2020)

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Sangseok You, Jeong-Hwan Kim, Sanghyun Lee, Vineet Kamat, Lionel Robert. Enhancing Perceived Safety in Human–Robot Collaborative Construction Using Immersive Virtual Environments. 2018. ⟨hal-02895952⟩

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