Safe Human-Robot Teaming through User-Adaptive Interaction
For humans to collaborate effectively and safely on shared tasks in human-machine teams, they need to be able to develop a trusting, working relationship. To do this, partners need to have a mutual understanding of the task and understand what the other party can and can’t do. As robotic systems become more human-like and autonomous, this relationship with humans becomes more important; because once established, human-machine teams will need to be more efficient and more robust to be able to safely handle problematic situations, for example, when failure occurs, be it on the system or human side.
This project will take into account the human’s social functioning level with respect to human-machine teaming. One way of measuring these levels in operators is though the validated Autism-Spectrum Quotient (AQ) questionnaire. This project will explore the hypothesis that those higher on the AQ scale will have a mental model of the robot that will be less influenced by the manipulation of human-robot interaction such as dialogue features and touch, as shown with human-human interaction. This will allow for safer human-like robotic behaviour that will adapt to the user’s social and communication skills level.
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