Research Papers - Dept of Information Technology

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/593

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Author: search.filters.author.Izumi, KSubject: search.filters.subject.Natural language commands

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Now showing 1 - 3 of 3
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    PublicationOpen Access
    Voice-controlled modular fuzzy neural controller with enhanced user autonomy
    (Springer-Verlag, 2003-03) Pulasinghe, K; Watanabe, K; Kiguchi, K; Izumi, K
    In this article, a fuzzy neural network (FNN)- based approach is presented to interpret imprecise natural language (NL) commands for controlling a machine. This system, (1) interprets fuzzy linguistic information in NL commands for machines, (2) introduces a methodology to implement the contextual meaning of NL commands, and (3) recognizes machine-sensitive words from the running utterances which consist of both in-vocabulary and out-ofvocabulary words. The system achieves these capabilities through a FNN, which is used to interpret fuzzy linguistic information, a hidden Markov model-based key-word spotting system, which is used to identify machine-sensitive words among unrestricted user utterances, and a possible framework to insert the contextual meaning of words into the knowledge base employed in the fuzzy reasoning process. The system is a complete system integration which converts imprecise NL command inputs into their corresponding output signals in order to control a machine. The performance of the system specifications is examined by navigating a mobile robot in real time by unconditional speech utterances.
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    PublicationEmbargo
    Control of redundant manipulators by fuzzy linguistic commands
    (IEEE, 2003-08-04) Pulasinghe, K; Watanabe, K; Izumi, K; Kiguchi, K
    This paper presents a method of controlling redundant manipulator by spoken language commands consisting fuzzy linguistic information. The present system introduces the fuzzyneuro control paradigm to the contemporary speech controlled robotic systems, which are based on on-off control paradigm. The system is sensitive to the action activation commands, action modification commands, and action repetition commands of the human-robot conversation carried out by practical dialogues. C.redibility of the proposed system is experimentally proved by controlling a manipulator with seven degrees-of-freedom by fuzzy linguistic information enriched spoken language commands to perform an assembling task.
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    PublicationOpen Access
    Controlling a robot manipulator with fuzzy voice commands using a probabilistic neural network
    (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.