JRM Vol.27 No.5 pp. 563-570
doi: 10.20965/jrm.2015.p0563


Emotional Model for Robotic System Using a Self-Organizing Map Combined with Markovian Model

Wisanu Jitviriya, Masato Koike, and Eiji Hayashi

Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology
680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan

January 29, 2015
August 25, 2015
October 20, 2015
motivation module, self-organizing map (SOM), Markovian emotion model
Behavioral/emotional expression system

In our research, we have focused on investigating the application of brain-inspired technology by developing a robot with consciousness resembling that of a human being. The goal was to enhance intelligent behavior/emotion, and to facilitate communication between human beings and robots. We sought to increase the robot’s behavioral/emotional intelligence capabilities so that it could distinguish, adapt and react to changes in the environment. In this paper, we present a behavioral/emotional expression system designed to work automatically by two processes. The first is a classification of behavior and emotions by determining the winner node based on Self-Organizing Map (SOM) learning. For the second, we propose a stochastic emotion model based on Markov theory in which the probabilities of emotional state transition are updated with affective factors. Finally, we verified this model with a conscious behavior robot (Conbe-I), and confirmed the effectiveness of the proposed system with the experimental results in a realistic environment.

Cite this article as:
W. Jitviriya, M. Koike, and E. Hayashi, “Emotional Model for Robotic System Using a Self-Organizing Map Combined with Markovian Model,” J. Robot. Mechatron., Vol.27, No.5, pp. 563-570, 2015.
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Last updated on Nov. 12, 2018