Advances in robotic technologies and artificial intelligence are allowing robots to emerge from
research laboratories into our lives. Experiences with field applications show that we have
underestimated the importance of human-robot interaction (HRI) and that new problems arise in
HRI as robotic technologies expand. This thesis classifies HRI along four dimensions human,
robot, task, and world and illustrates that previous HRI classifications can be successfully
interpreted as either about one of these elements or about the relationship between two or more
of these elements. Current HRI studies of single-operator single-robot (SOSR) control and
single-operator multiple-robots (SOMR) control are reviewed using this approach.
Human control of multiple robots has been suggested as a way to improve effectiveness in
robot control. Unlike previous studies that investigated human interaction either in low-fidelity
simulations or based on simple tasks, this thesis investigates human interaction with cooperating
robot teams within a realistically complex environment. USARSim, a high-fidelity game-enginebased
robot simulator, and MrCS, a distributed multirobot control system, were developed for
this purpose. In the pilot experiment, we studied the impact of autonomy level. Mixed initiative
control yielded performance superior to fully autonomous and manual control.
To avoid limitation to particular application fields, the present thesis focuses on common
HRI evaluations that enable us to analyze HRI effectiveness and guide HRI design independently
of the robotic system or application domain. We introduce the interaction episode (IEP), which
was inspired by our pilot human-multirobot control experiment, to extend the Neglect Tolerance
HUMAN CONTROL OF COOPERATING ROBOTS
Jijun Wang, Ph.D.
University of Pittsburgh, 2007
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model to support general multiple robots control for complex tasks. Cooperation Effort (CE),
Cooperation Demand (CD), and Team Attention Demand (TAD) are defined to measure the
cooperation in SOMR control. Two validation experiments were conducted to validate the CD
measurement under tight and weak cooperation conditions in a high-fidelity virtual environment.
The results show that CD, as a generic HRI metric, is able to account for the various factors that
affect HRI and can be used in HRI evaluation and analysis.
Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-01072008-135804 |
Date | 31 January 2008 |
Creators | Wang, Jijun |
Contributors | Paul Scerri, Michael Lewis, Katia Sycara, Paul Munro, Michael Spring |
Publisher | University of Pittsburgh |
Source Sets | University of Pittsburgh |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.library.pitt.edu/ETD/available/etd-01072008-135804/ |
Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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