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JACIII Vol.17 No.5 pp. 753-760
doi: 10.20965/jaciii.2013.p0753
(2013)

Paper:

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Recognition of Indoor Environment by Robot Partner Using Conversation

Jinseok Woo and Naoyuki Kubota

Graduate School of System Design, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan

Received:
March 20, 2013
Accepted:
July 4, 2013
Published:
September 20, 2013
Creative Commons License
Keywords:
simultaneous localization and mapping, robot partner, neural network, genetic algorithm
Abstract
To support daily life before performing an action, a robot partner must perceive an unknown environment. Much research has been done from various viewpoints on self-localization estimation and environment perception. In our research, the robot partner performs self-localization and environment recognition using Simultaneous Localization and Mapping for self-localization estimation and map building. In this paper, we propose a method for recognizing indoor environments by robot partners based on conversations with human beings. Information acquired from maps is identified in order to share the meaning with human beings after the required interpretation. In this paper, we therefore propose a method for recognizing environmental maps by labeling these maps based on symbolic information developed through conversation with human beings. The proposed method is composed of four parts. First, the robot partner applies a steady-state genetic algorithm for self-localization estimation. Second, we use a map building algorithm for expressing the topological map. Third, conversation with human beings is performed for acquiring symbolic information in order to recognize object and position locations through the map. Fourth, we perform experiments and discuss the effectiveness of the proposed technique.
Cite this article as:
J. Woo and N. Kubota, “Recognition of Indoor Environment by Robot Partner Using Conversation,” J. Adv. Comput. Intell. Intell. Inform., Vol.17 No.5, pp. 753-760, 2013.
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