  Increasingly complex and autonomous robots are being deployed in real-world
environments with far-reaching consequences. High-stakes scenarios, such as
emergency response or offshore energy platform and nuclear inspections, require
robot operators to have clear mental models of what the robots can and can't
do. However, operators are often not the original designers of the robots and
thus, they do not necessarily have such clear mental models, especially if they
are novice users. This lack of mental model clarity can slow adoption and can
negatively impact human-machine teaming. We propose that interaction with a
conversational assistant, who acts as a mediator, can help the user with
understanding the functionality of remote robots and increase transparency
through natural language explanations, as well as facilitate the evaluation of
operators' mental models.
