Controlling a robot manipulator with fuzzy voice commands using a probabilistic neural network

Chandimal Jayawardena, Keigo Watanabe, Kiyotaka Izumi

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)


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 coach-player 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.

Original languageEnglish
Pages (from-to)155-166
Number of pages12
JournalNeural Computing and Applications
Issue number2
Publication statusPublished - Feb 1 2007
Externally publishedYes


  • Coach-player system
  • Natural language commands
  • PNN
  • Sub-coach
  • Subjective decisions

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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