Abstract

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.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2015

Semester

Fall

Advisor

Szalma, James

Degree

Doctor of Philosophy (Ph.D.)

College

College of Sciences

Department

Psychology

Degree Program

Psychology; Human Factors Psychology

Format

application/pdf

Identifier

CFE0006403

URL

http://purl.fcla.edu/fcla/etd/CFE0006403

Language

English

Release Date

June 2021

Length of Campus-only Access

5 years

Access Status

Doctoral Dissertation (Campus-only Access)

Share

COinS