Assessing physical workload for human-robot peer-based teams

  • Authors:
  • Caroline E. Harriott;Tao Zhang;Julie A. Adams

  • Affiliations:
  • -;-;-

  • Venue:
  • International Journal of Human-Computer Studies
  • Year:
  • 2013

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Abstract

Peer-based human-robot teams involve both teammates working in the same physical space and contributing to the same goals. Predictions of human performance based upon environmental, internal, task and organizational influences have proven useful, but these predictive methods have not yet been proven to apply to human-robot peer-based team situations. Physical workload is an important component of overall workload and influences human performance. The presented research examines physical workload metrics, appraises predictive models of physical workload, and investigates the impact of human-robot peer-based teaming situations on physical workload. Two evaluations are presented. The Guided evaluation required participants to follow guided instructions provided by a partner, either a remotely located human or a locally situated robot. The Collaborative evaluation required collaboration and teaming with joint decisions with either the locally situated human or robot partner. The results from both evaluations show that overall workload and subjectively rated physical workload was lower for the human-robot teams than the human-human teams; however, the physiologically measured physical workload was higher for the human-robot teams. The lack of a collocated human partner during the Guided evaluation did not affect the workload results. The modeling techniques and empirical measures used in the evaluations can be extended to other human-robot team situations.