With the development in robotics and the increasing deployment of robots, human-robot teams are set to be a mainstay in the future. However, our understanding of the effectiveness and impact of this new form of teaming is limited. Previous experience with technology and automa-tion has shown that technological aids do not always result in the intended consequences of im-proved performance and alleviation of workload and stress. No doubt a large part of this is due to the fact that the relationships among taskload, workload and performance are complex as hu-man operators interact dynamically with tasks and technology. Measures of workload are also varied and differentially sensitive. There is also the added challenge posed by multi-tasking envi-ronments which typify most real-world situations. Given all this, efforts in designing technologi-cal aids, such as an adaptive robot aid in the context of human-robot teaming, would require a workload model that reflects the intricate relationship between taskload and the individual opera-tor's experience of workload. Such a model can then be used to drive a closed-loop system on which adaptive robot aiding can be based. The present research sought to investigate the effec-tiveness of a closed-loop system, based on a model of workload, in enhancing performance in a simulated military mission involving a human-robot team. Results showed that adaptive robot aid driven by workload needs as assessed by physiological measures resulted in greater improve-ments in performance compared to robot aid that was imposed by the system.
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Doctor of Philosophy (Ph.D.)
College of Sciences
Psychology; Human Factors Psychology
Length of Campus-only Access
Doctoral Dissertation (Campus-only Access)
Teo, Grace, "Enhancing the effectiveness of Human-Robot teaming with a closed-loop system" (2015). Electronic Theses and Dissertations, 2004-2019. 5160.