CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
research
Teams organization and performance analysis in autonomous human-robot teams
Authors
SY Chien
M Lewis
H Wang
Publication date
1 January 2010
Publisher
'Association for Computing Machinery (ACM)'
Doi
Cite
Abstract
This paper proposes a theory of human control of robot teams based on considering how people coordinate across different task allocations. Our current work focuses on domains such as foraging in which robots perform largely independent tasks. The present study addresses the interaction between automation and organization of human teams in controlling large robot teams performing an Urban Search and Rescue (USAR) task. We identify three subtasks: perceptual search-visual search for victims, assistance-teleoperation to assist robot, and navigation-path planning and coordination. For the studies reported here, navigation was selected for automation because it involves weak dependencies among robots making it more complex and because it was shown in an earlier experiment to be the most difficult. This paper reports an extended analysis of the two conditions from a larger four condition study. In these two "shared pool" conditions Twenty four simulated robots were controlled by teams of 2 participants. Sixty paid participants (30 teams) were recruited to perform the shared pool tasks in which participants shared control of the 24 UGVs and viewed the same screens. Groups in the manual control condition issued waypoints to navigate their robots. In the autonomy condition robots generated their own waypoints using distributed path planning. We identify three self-organizing team strategies in the shared pool condition: joint control operators share full authority over robots, mixed control in which one operator takes primary control while the other acts as an assistant, and split control in which operators divide the robots with each controlling a sub-team. Automating path planning improved system performance. Effects of team organization favored operator teams who shared authority for the pool of robots. © 2010 ACM
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Crossref
See this paper in CORE
Go to the repository landing page
Download from data provider
info:doi/10.1145%2F2377576.237...
Last time updated on 05/06/2019
Name not available
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:d-scholarship.pitt.edu:591...
Last time updated on 23/11/2016
D-Scholarship@Pitt
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:d-scholarship.pitt.edu:591...
Last time updated on 19/07/2013
Name not available
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:d-scholarship.pitt.edu:591...
Last time updated on 15/12/2016