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

Scalable target detection for large robot teams

Wang, H and Kolling, A and Abedin, S and Lee, PJ and Chien, SY and Lewis, M and Brooks, N and Owens, S and Scerri, P and Sycara, K (2011) Scalable target detection for large robot teams. In: UNSPECIFIED.

[img] PDF (upload from ACM)
Published Version
Available under License : See the attached license file.

Download (2MB)
[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


In this paper, we present an asynchronous display method, coined image queue, which allows operators to search through a large amount of data gathered by autonomous robot teams. We discuss and investigate the advantages of an asynchronous display for foraging tasks with emphasis on Urban Search and Rescue. The image queue approach mines video data to present the operator with a relevant and comprehensive view of the environment in order to identify targets of interest such as injured victims. It fills the gap for comprehensive and scalable displays to obtain a network-centric perspective for UGVs. We compared the image queue to a traditional synchronous display with live video feeds and found that the image queue reduces errors and operator's workload. Furthermore, it disentangles target detection from concurrent system operations and enables a call center approach to target detection. With such an approach we can scale up to very large multi-robot systems gathering huge amounts of data that is then distributed to multiple operators. Copyright 2011 ACM.


Social Networking:
Share |


Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Wang, H
Kolling, A
Abedin, Ssha33@pitt.eduSHA33
Lee, PJ
Chien, SY
Lewis, M
Brooks, N
Owens, S
Scerri, P
Sycara, K
Date: 1 April 2011
Date Type: Publication
Journal or Publication Title: HRI 2011 - Proceedings of the 6th ACM/IEEE International Conference on Human-Robot Interaction
Page Range: 363 - 370
Event Type: Conference
DOI or Unique Handle: 10.1145/1957656.1957792
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781450305617
Other ID: 10.1145/1957656.1957792 (DOI)
Date Deposited: 22 Jun 2011 16:17
Last Modified: 08 Feb 2024 11:55


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item