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Gal A. Kaminka and Yehuda Elmaliach.
Single Operator, Multiple Robots: Call-Request Handling in Tight-Coordination Tasks. In Distributed Autonomous
Robotic Systems 7, Springer-Verlag, 2006.
Many applications of robots require a human operator to superviseand operate multiple robots. In particular, the operator may be requiredto resolve call requests when robots require assistance. Previousinvestigations assume that robots are independent of each other, andallow the operator to resolve one request at a time. However, keychallenges and opportunities arise when robots work in tightly-coordinatingteams. Robots depend on each other, and thus a single failing robotmay cause multiple call requests to be issued (by different robots).Moreover, when the operator switches control to a robot, its teammatesmust often wait idly until the call request is resolved. Wecontrast previous approaches with two novel distributed methods, wherethe call-request resolution is itself considered a collaborative problem-solvingactivity, and non-failingrobots use their knowledge of the coordination to assist the operator.We empirically compare the different approaches in several scenarios involvingtight coordination, where an operator seeks a dead robot in orderto assist it. Extensive experiments with 25 human operators show thatthis new technique is superior to existing methods, in terms of reducingthe time to locate the dead robot. We also show that the new methodhas much more consistent performance across different operators.
@InCollection{dars06yehuda,
author = {Gal A. Kaminka and Yehuda Elmaliach},
title = {Single Operator, Multiple Robots: Call-Request Handling in Tight-Coordination Tasks},
booktitle = {Distributed Autonomous Robotic Systems 7},
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publisher = {Springer-Verlag},
year = {2006},
abstract = {Many applications of robots require a human operator to supervise
and operate multiple robots. In particular, the operator may be required
to resolve call requests when robots require assistance. Previous
investigations assume that robots are independent of each other, and
allow the operator to resolve one request at a time. However, key
challenges and opportunities arise when robots work in tightly-coordinating
teams. Robots depend on each other, and thus a single failing robot
may cause multiple call requests to be issued (by different robots).
Moreover, when the operator switches control to a robot, its teammates
must often wait idly until the call request is resolved. We
contrast previous approaches with two novel distributed methods, where
the call-request resolution is itself considered a collaborative problem-solving
activity, and non-failing
robots use their knowledge of the coordination to assist the operator.
We empirically compare the different approaches in several scenarios involving
tight coordination, where an operator seeks a dead robot in order
to assist it. Extensive experiments with 25 human operators show that
this new technique is superior to existing methods, in terms of reducing
the time to locate the dead robot. We also show that the new method
has much more consistent performance across different operators.
},
wwwnote = {},
OPTeditor = {},
OPTvolume = {},
OPTnumber = {},
OPTseries = {},
OPTtype = {},
OPTchapter = {},
OPTaddress = {},
OPTedition = {},
OPTmonth = {},
OPTnote = {},
OPTannote = {}
}
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