Task teaching system for a force-controlled parallel robot using multiple teaching modes with human demonstration data

Daisuke Sato, Ryosuke Kobayashi, Akira Kobayashi, Masaru Uchiyama

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    A purpose of this paper is to expedite onerous initial procedures when a force-controlled parallel robot is taught task motions by the off-line task teaching/playback system which we have developed to realize the motion planning suitable for tasks and playback task motions dexterously. In this teaching system, the numerical teaching method has been employed to give detailed descriptions of the motion parameters, but it brings out a trade-off between fine-tuning and complication. Therefore, new devices and functions are added to the teaching system and multiple teaching modes are implemented for solving this problem. The main feature is the use of task teaching with human demonstration data which are obtained in real and virtual human motion measurement systems. The initial teaching data are generated by the demonstration data and the robot commands are converted into them with the control parameters. Typical task is demonstrated and we verify the effectiveness of the teaching modes experimentally.

    Original languageEnglish
    Title of host publicationProceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006
    Pages3960-3965
    Number of pages6
    DOIs
    Publication statusPublished - 2006 Dec 27
    Event2006 IEEE International Conference on Robotics and Automation, ICRA 2006 - Orlando, FL, United States
    Duration: 2006 May 152006 May 19

    Publication series

    NameProceedings - IEEE International Conference on Robotics and Automation
    Volume2006
    ISSN (Print)1050-4729

    Other

    Other2006 IEEE International Conference on Robotics and Automation, ICRA 2006
    CountryUnited States
    CityOrlando, FL
    Period06/5/1506/5/19

    ASJC Scopus subject areas

    • Software
    • Control and Systems Engineering
    • Artificial Intelligence
    • Electrical and Electronic Engineering

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