JRM Vol.17 No.6 pp. 697-704
doi: 10.20965/jrm.2005.p0697


A Dialogue Control Model Based on Ambiguity Evaluation of Users’ Instructions and Stochastic Representation of Experiences

Tetsunari Inamura, Masayuki Inaba, and Hirochika Inoue

Dept. of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan

February 3, 2005
July 11, 2005
December 20, 2005
human-robot interaction, Bayesian networks, dialogue planning, user adaptation, experience based behavior
To operate in everyday environments, robots much accomplish complex tasks following often mbiguous and uncertain instructions, mainly through advanced inference or recognition. We focus on an intelligent human-robot interaction framework that reduces the burden of the user. Robots compensate for ambiguities by active sensing and dialogue control through questions and suggestions to users. Robots also use experience to reduce the user’s burden. We propose a criterion for ambiguity evaluation of user instructions, stochastic representation of personal experiences and a dialogue control model for accomplishing tasks in complex environments. We demonstrate the feasibility of our proposal in demonstrate experiment where a robot searches for an object in disorganized work space with ambiguous instructions.
Cite this article as:
T. Inamura, M. Inaba, and H. Inoue, “A Dialogue Control Model Based on Ambiguity Evaluation of Users’ Instructions and Stochastic Representation of Experiences,” J. Robot. Mechatron., Vol.17 No.6, pp. 697-704, 2005.
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