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A Human Factors Analysis of Proactive Support in Human-Robot Teaming

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Arizona State University Tempe United States

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It has long been assumed that for effective human robot teaming, it is desirable for assistive robots to infer the goals and intents of the humans, and take proactive actions to help them achieve their goals. However, there has not been any systematic evaluation of the accuracy of this claim. On the face of it, there are several ways a proactive robot assistant can in fact reduce the effectiveness of teaming. For example, it can increase the cognitive load of the human teammate by performing actions that are unanticipated by the human. In such cases, even though the teaming performance could be improved, it is unclear whether humans are willing to adapt to robot actions or are able to adapt in a timely manner. Furthermore, misinterpretations and delays in goal and intent recognition due to partial observations and limited communication can also reduce the performance. In this paper, our aim is to perform an analysis of human factors on the effectiveness of such proactive support in human-robot teaming.

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Conference Paper

Supplementary Note:

IEEE/RSJ Intl. Conference on Intelligent Robots and Systems , 28 Sep 2015, 02 Oct 2015,



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Approved For Public Release;

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