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Full-Text Articles in Physical Sciences and Mathematics
Beyond Robot Fan-Out: Towards Multi-Operator Supervisory Control, Michael A. Goodrich, Yisong Guo, Jonathan M. Whetten
Beyond Robot Fan-Out: Towards Multi-Operator Supervisory Control, Michael A. Goodrich, Yisong Guo, Jonathan M. Whetten
Faculty Publications
This paper explores multi-operator supervisory control (MOSC) of multiple independent robots using two complementary approaches: a human factors experiment and an agent-based simulation. The experiment identifies two task and environment limitations on MOSC: task saturation and task diffusion. It also identifies the correlation between task specialization and performance, and the possible existence of untapped spare capacity that emerges when multiple operators coordinate. The presence of untapped spare capacity is explored using agent-based simulation, resulting in evidence which suggests that operators may be more effective when they operate at less than maximum capacity.
Human–Robot Interaction: A Survey, Michael A. Goodrich, Alan C. Schultz
Human–Robot Interaction: A Survey, Michael A. Goodrich, Alan C. Schultz
Faculty Publications
Human–Robot Interaction (HRI) has recently received considerable attention in the academic community, in labs, in technology companies, and through the media. Because of this attention, it is desirable to present a survey of HRI to serve as a tutorial to people outside the field and to promote discussion of a unified vision of HRI within the field. The goal of this review is to present a unified treatment of HRI-related problems, to identify key themes, and discuss challenge problems that are likely to shape the field in the near future. Although the review follows a survey structure, the goal of …
Metrics For Evaluating Human-Robot Interactions, Michael A. Goodrich, Dan R. Olsen Jr.
Metrics For Evaluating Human-Robot Interactions, Michael A. Goodrich, Dan R. Olsen Jr.
Faculty Publications
Metrics for evaluating the quality of a human-robot interface are introduced. The autonomy of a robot is measured by its neglect time. The robot attention demand metric measures how much of the user’s attention is involved with instructing a robot. The free-time and fan-out metrics are two ways to measure this demand. Each of them leads to estimates of the interaction effort. Reducing interaction effort without diminishing task effectiveness is the goal of human-robot interaction design.