Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Imperfect Automation in Scheduling Operator Attention on Control of Multi-Robots

Chien, Shih-Yi and Lewis, Michael and Mehrotra, Siddharth and Sycara, Katia (2013) Imperfect Automation in Scheduling Operator Attention on Control of Multi-Robots. In: UNSPECIFIED.

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


<jats:p> An operator’s workload increases substantially when the operator must control multiple robots and continually shift attention from robot to robot. As the number of robots increases, the amount of time an operator can spend operating any particular robot decreases, which leads to inevitable changes in the robot’s performance. If the robots could self-report encountered faults, the operator could conserve cognitive resources to spend on reasoning about more complex situations. In the reported experiment, participants performed foraging tasks while assisted by an alarmed system, either Open-queue in which all alarms are displayed or SJF-queue (shortest-job-first), whose reliability level was high (90%) or low (50%) under different task load (3-robots vs. 6-robots). The results showed that simply increasing the system reliability might not effectively contribute to the overall performance or the participants’ trust in automation. An inverse relationship was observed between experienced workload and rated trust which also amplified the effects of imperfect automation. </jats:p>


Social Networking:
Share |


Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Chien, Shih-Yi
Lewis, Michael
Mehrotra, Siddharth
Sycara, Katia
Date: September 2013
Date Type: Publication
Journal or Publication Title: Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Volume: 57
Number: 1
Publisher: SAGE Publications
Page Range: 1169 - 1173
Event Type: Conference
DOI or Unique Handle: 10.1177/1541931213571260
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISSN: 2169-5067
Date Deposited: 16 Jun 2014 17:05
Last Modified: 16 May 2021 14:55


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item