Human-robot communication using multiple recurrent neural networks

Yoshihiro Sakamoto, Tetsuya Ogata, Shigeki Sugano

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

    Abstract

    On the methodology of robotic design from the traditional view of communication which is assumed as a symbol process, robots are forced to confront the symbol grounding problem. However, if communication is assumed as the analog dynamics and robots are driven by it, robots can avoid the problem and be situated in the environment and to other agents. In this paper we will introduce a new communication system constructed from the view of dynamical systems to achieve the situatedness. This system is that there is a robot in a virtual environment and the control of the robot is shared by human operation using a joystick and a robot controller. As the controller, we adopt multiple recurrent neural networks (MRNN) which are able to cope with complex environments and broad communication that single recurrent net cannot cope with. We conduct two experiments in order to evaluate the effectiveness of MRNN to a low level communication task such as nonverbal interaction. First, we examine the effect of the number of RNNs contained in MRNN. Second, we examine the effect of the context dependency of MRNN. These experiments show the capability of MRNN as a new-type controller of communication robot.

    Original languageEnglish
    Title of host publication2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    Pages1574-1579
    Number of pages6
    Volume2
    Publication statusPublished - 2004
    Event2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - Sendai
    Duration: 2004 Sep 282004 Oct 2

    Other

    Other2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    CitySendai
    Period04/9/2804/10/2

    Fingerprint

    Recurrent neural networks
    Robots
    Communication
    Controllers
    Electric grounding
    Virtual reality
    Communication systems
    Dynamical systems
    Robotics
    Experiments

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Sakamoto, Y., Ogata, T., & Sugano, S. (2004). Human-robot communication using multiple recurrent neural networks. In 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (Vol. 2, pp. 1574-1579)

    Human-robot communication using multiple recurrent neural networks. / Sakamoto, Yoshihiro; Ogata, Tetsuya; Sugano, Shigeki.

    2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vol. 2 2004. p. 1574-1579.

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

    Sakamoto, Y, Ogata, T & Sugano, S 2004, Human-robot communication using multiple recurrent neural networks. in 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). vol. 2, pp. 1574-1579, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sendai, 04/9/28.
    Sakamoto Y, Ogata T, Sugano S. Human-robot communication using multiple recurrent neural networks. In 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vol. 2. 2004. p. 1574-1579
    Sakamoto, Yoshihiro ; Ogata, Tetsuya ; Sugano, Shigeki. / Human-robot communication using multiple recurrent neural networks. 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vol. 2 2004. pp. 1574-1579
    @inproceedings{9fa58b0351b74785bbd4cd5798399b15,
    title = "Human-robot communication using multiple recurrent neural networks",
    abstract = "On the methodology of robotic design from the traditional view of communication which is assumed as a symbol process, robots are forced to confront the symbol grounding problem. However, if communication is assumed as the analog dynamics and robots are driven by it, robots can avoid the problem and be situated in the environment and to other agents. In this paper we will introduce a new communication system constructed from the view of dynamical systems to achieve the situatedness. This system is that there is a robot in a virtual environment and the control of the robot is shared by human operation using a joystick and a robot controller. As the controller, we adopt multiple recurrent neural networks (MRNN) which are able to cope with complex environments and broad communication that single recurrent net cannot cope with. We conduct two experiments in order to evaluate the effectiveness of MRNN to a low level communication task such as nonverbal interaction. First, we examine the effect of the number of RNNs contained in MRNN. Second, we examine the effect of the context dependency of MRNN. These experiments show the capability of MRNN as a new-type controller of communication robot.",
    author = "Yoshihiro Sakamoto and Tetsuya Ogata and Shigeki Sugano",
    year = "2004",
    language = "English",
    isbn = "0780384636",
    volume = "2",
    pages = "1574--1579",
    booktitle = "2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)",

    }

    TY - GEN

    T1 - Human-robot communication using multiple recurrent neural networks

    AU - Sakamoto, Yoshihiro

    AU - Ogata, Tetsuya

    AU - Sugano, Shigeki

    PY - 2004

    Y1 - 2004

    N2 - On the methodology of robotic design from the traditional view of communication which is assumed as a symbol process, robots are forced to confront the symbol grounding problem. However, if communication is assumed as the analog dynamics and robots are driven by it, robots can avoid the problem and be situated in the environment and to other agents. In this paper we will introduce a new communication system constructed from the view of dynamical systems to achieve the situatedness. This system is that there is a robot in a virtual environment and the control of the robot is shared by human operation using a joystick and a robot controller. As the controller, we adopt multiple recurrent neural networks (MRNN) which are able to cope with complex environments and broad communication that single recurrent net cannot cope with. We conduct two experiments in order to evaluate the effectiveness of MRNN to a low level communication task such as nonverbal interaction. First, we examine the effect of the number of RNNs contained in MRNN. Second, we examine the effect of the context dependency of MRNN. These experiments show the capability of MRNN as a new-type controller of communication robot.

    AB - On the methodology of robotic design from the traditional view of communication which is assumed as a symbol process, robots are forced to confront the symbol grounding problem. However, if communication is assumed as the analog dynamics and robots are driven by it, robots can avoid the problem and be situated in the environment and to other agents. In this paper we will introduce a new communication system constructed from the view of dynamical systems to achieve the situatedness. This system is that there is a robot in a virtual environment and the control of the robot is shared by human operation using a joystick and a robot controller. As the controller, we adopt multiple recurrent neural networks (MRNN) which are able to cope with complex environments and broad communication that single recurrent net cannot cope with. We conduct two experiments in order to evaluate the effectiveness of MRNN to a low level communication task such as nonverbal interaction. First, we examine the effect of the number of RNNs contained in MRNN. Second, we examine the effect of the context dependency of MRNN. These experiments show the capability of MRNN as a new-type controller of communication robot.

    UR - http://www.scopus.com/inward/record.url?scp=14044275128&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=14044275128&partnerID=8YFLogxK

    M3 - Conference contribution

    SN - 0780384636

    VL - 2

    SP - 1574

    EP - 1579

    BT - 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

    ER -