(Springer-Verlag, 2006-07-06) Jayawardena, C; Watanabe, K; Izumi, K
Natural language commands are generated by
intelligent human beings. As a result, they contain a lot
of information. Therefore, if it is possible to learn from
such commands and reuse that knowledge, it will be a
very efficient process. In this paper, learning from such
information rich voice commands for controlling a
robot is studied. First, new concepts of fuzzy coachplayer system and sub-coach are proposed for controlling robots with natural language commands. Then, the
characteristics of the subjective human decision making
process are discussed and a Probabilistic Neural
Network (PNN) based learning method is proposed to
learn from such commands and to reuse the acquired
knowledge. Finally, the proposed concept is demonstrated and confirmed with experiments conducted using
a PA-10 redundant manipulator.
