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Asynchronous control with ATR for large robot teams

Brooks, N and Scerri, P and Sycara, K and Wang, H and Chien, SY and Lewis, M (2011) Asynchronous control with ATR for large robot teams. In: UNSPECIFIED.

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Abstract

In this paper, we discuss and investigate the advantages of an asynchronous display, called "image queue", tested for an urban search and rescue foraging task. The image queue approach mines video data to present the operator with a relevant and comprehensive view of the environment by selecting a small number of images that together cover large portions of the area searched. This asynchronous approach allows operators to search through a large amount of data gathered by autonomous robot teams, and allows comprehensive and scalable displays to obtain a network-centric perspective for unmanned ground vehicles (UGVs). In the reported experiment automatic target recognition (ATR) was used to augment utilities based on visual coverage in selecting imagery for presentation to the operator. In the cued condition a box was drawn in the region in which a possible target was detected. In the no-cue condition no box was drawn although the target detection probability continued to play a role in the selection of imagery. We found that operators using the image queue displays missed fewer victims and relied on teleoperation less often than those using streaming video. Image queue users in the no-cue condition did better in avoiding false alarms and reported lower workload than those in the cued condition. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Brooks, N
Scerri, P
Sycara, K
Wang, H
Chien, SY
Lewis, M
Date: 28 November 2011
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Proceedings of the Human Factors and Ergonomics Society
Page Range: 444 - 448
Event Type: Conference
DOI or Unique Handle: 10.1177/1071181311551091
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9780945289395
ISSN: 1071-1813
Date Deposited: 15 Jun 2012 19:51
Last Modified: 02 Feb 2019 16:58
URI: http://d-scholarship.pitt.edu/id/eprint/12401

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