Abstract
In this paper, we aim to demonstrate the potential for wider-ranging capabilities and ease of transferability of our recently developed decision-making architecture for human-robot collaboration. To this end, a somewhat related but different application-specific example from the generic one used in its development is chosen, a toy car assembling task in which a participant works together with a robot to perform the assembly task. In a “Wizard of Oz” fashion, a comparison is made between the participant’s reactions to working with the robot being controlled either by our architecture or by a human “Wizard” who is hidden from view. With regard to the generalisability of the architecture, we also wish to investigate whether specific models trained on the observed human behaviour in a generic assembly task also transfer to this more complex task. Therefore, pre-trained interaction models from a prior generic pick-and-place task are used again in this new application without any re-traini (More)