Principles of Adjustable Interactions

Jacob W. Crandall and Michael A. Goodrich

In this paper, we seek to model natural human-robot interactions in human-robot teams that support adjustable autonomy and interactions. We present a theoretical characterization of interaction efficiency. We then perform case studies to validate this theoretical framework. Specifically, in one case study we compare interaction efficiency between a shared control teleoperation algorithm and traditional manual-control teleoperation. We then perform another case study in which we analyze the neglect tolerance of a point-topoint interaction scheme. The principles learned from these case studies should help to build more effective human-robot systems.

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