In this paper, we propose to examine the practices of leadership defined in human relationships and model their use in maximizing performance for human-robot interaction scenarios. This process involves first defining the human-robot space of interaction and mapping the situational context in which human leadership styles are most fitting. We then determine which behavior, for both the human and robot, is most appropriate in order to understand the proper roles for human-robot integration. From there, we model the necessary robot behavior for increasing efficiency in human-robot interaction schemes. We conclude by discussing experimental results derived from allocating roles in representative human-robot navigation scenarios.

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