Autonomous Action Generation of Humanoid Robot from Natural Language

  • Hirokazu Watabe
  • Tsukasa Kawaoka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4251)


Communication between human and robot is necessary for an intelligent robot to be active in daily life. Conversation is the basis of communication. Most of the instructions given to a robot are related to some actions. This paper reports the method to generate the action of the humanoid robot by conversation. For this purpose, comprehension of action instruction written by natural language is necessary. The system to understand natural language for generating action is proposed. This system consists of a semantic understanding method to arrange input information, the knowledge base of vocabulary related to actions, the knowledge base of the parameter for robots to act, and association mechanism to handle a word, which is not known. The system is capable of understanding many input sentences by the association mechanism using Concept-Base and a degree of association.


Natural Language Body Part Basic Action Humanoid Robot Semantic Meaning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Ishiguro, H., Ono, T., Imai, M., Kanda, T.: Development of an Interactive Humanoid Robot “Robovie” – An interdisciplinary approach. In: Robotics Research. STAR 6, pp. 179–191. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  2. 2.
    Kojima, K., Watabe, H., Kawaoka, T.: Concept-base Refining with Thesaurus and Logical Relations for a Word Association-system. In: Proc. of KES 2001, Part 2, pp. 1590–1594 (2001)Google Scholar
  3. 3.
    Watabe, H., Kawaoka, T.: The Degree of Association between Concepts using the Chain of Concepts. In: Proc. of SMC 2001, pp. 877–881 (2001)Google Scholar
  4. 4.
    Goldberg, D.E.: Genetic Algorithms in Search. Optimization and Machine Learning. Addison-Wesley, Reading (1989)MATHGoogle Scholar
  5. 5.
    Shinohara, Y., Watabe, H., Kawaoka, T.: A Conversation Semantic Understanding Method using the Commonsense Judgment System, IPSJ SIG Notes, NL-153, pp. 89–96 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hirokazu Watabe
    • 1
  • Tsukasa Kawaoka
    • 1
  1. 1.Dept. of Knowledge Engineering & Computer SciencesDoshisha UniversityKyo-Tanabe, KyotoJapan

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