Challenge: Concept of system life and its application to robotics

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Abstract

Artifact systems created by humans interact with the surrounding natural world and have a large-scale influence on our human lives. The most creditable concept to this critical issue of scientific and technological development seems to be “System Life” that is an innovative competence to be embodied into any artifact system for creating harmony in the world of natural entities and artifact systems interacting with each other. System life is defined as a seamless system of sensing, processing, activating and expressing mechanisms governed by system life information. This paper introduces a design approach of robots possessing system life. First, this paper presents the concept of system life comparing it with the conventional design methodology of intelligent systems. Second, the paper introduces an intelligent control methodology using the cubic neural network that the author developed in order to cope with unpredicted failures. Finally, the paper presents various intelligent robots, a skiing robot, autonomous soccer robots, a game playing robot, as new concrete artifact systems designed using the system life concept.

Introduction

In 2003, the Center of Excellence proposed by Keio university and titled “System Design: Paradigm Shift from Intelligence to Life” was selected and started. This Center of Excellence aims at establishing a global collaborative and educational research center based on the concept of system design engineering which was initiated by Keio University. In this Center of Excellence, an important role will be played in the fields of mechanical and architectural engineering by leading in the 21st century a paradigm shift to life for the engineering methods developed historically from high performance and intelligence technology in the 20th century. Fig. 1 illustrates the evolution of technology.

In order to create harmony in the world of the natural entities and artifact systems interacting with each other, this Center of Excellence focuses on the characteristics of life as a system as well as various life functions and creates a new design methodology of mechanical and architectural systems which are enabled to be interactive with external systems by embedding design information, including rules of interaction, in the inner components of the artifacts.

To achieve the objective of this Center of Excellence, the system design engineering will be further developed as a backbone of the Center of Excellence and several product innovations with respect to architecture, robotics, bio/energy system and so on will be explored.

The artifact systems created by humans generate a deep and huge interaction with the surrounding natural world and have a large-scale influence on our human lives. The most creditable concept to this critical issue of scientific and technological development seems to be “System Life”, that is an innovative competence to be embodied into any artifact system for creating harmony in the world of the natural entities and artifact systems interacting with each other. System life is defined as a seamless fusion system of sensing, processing, activating and expressing mechanisms governed by system life information, as shown in Fig. 2.

This paper introduces a design approach of robots possessing system life. First, the paper presents the concept of system life comparing it with the conventional design methodology. Second, an intelligent control methodology using the cubic neural network that the author developed will be introduced in order to cope with unpredicted failures. Finally, the paper presents various intelligent robots, a skiing robot, autonomous soccer robots, and a game playing robot as new concrete artifact systems designed using the system life concept.

Section snippets

Concept of system life

There has been no concept of life in artifacts except for artificial life and computer viruses. Users of machines are humans and machines are regarded as tools for humans. However, programmed intelligent machines play more influential roles than humans expect and humans have become strongly influenced by machines. This trend will become stronger and we will face the limitations of conventional design approaches and procedures.

There is a natural principle that the more intelligent animals are,

Design of intelligent systems

In the previous section, the features of life are characterized by their functions. Here, they are characterized from the side of biology.

  • Autonomy

  • Metabolism, immunity

  • Self-organization

  • Homeostasis

  • Adaptation to environment

  • Stability to disturbance

  • Storage of information

  • Learning, memory

  • Generation, self-reproduction

  • Heredity

  • Evolution, growth ability

  • Aging, apoptosis

  • Death

The above features are also nothing but aspects of life phenomena. The common information on various aspects is embedded in genes. In

Conclusions

This paper introduced the concepts of system life and various robot design methods based on this concept. Particularly, the importance of the method for integrating the various aspects was indicated. Our challenge is still primitive and this is only the first step to a system design aiming at a paradigm shift from intelligence to life. We have to keep learning how to achieve system integration from natural systems, since life is not a function but a system. We explored a systematic approach of

Kazuo Yoshida received B.E. and M.E. degrees in the Department of System Design Engineering from Keio University in 1973 and 1975, respectively. He received the Dr. Eng. degree from Keio University, Yokohama, Japan, in 1978. In 1981, he started working as a Research Assistant of the Department of Mechanical Engineering, Keio University, Yokohama, Japan, where he became an Associate Professor in 1984 and a Professor in 1994. From 1996 to 2008, he was a Professor at the Department of System

References (8)

  • R.E. Fikes et al.

    STRIPS: a new approach to the application of theorem proving to problem solving

    Artificial Intelligence

    (1971)
  • H. Kidoshi et al.

    Intelligent control method using cubic neural network (Intelligent nonlinear control of pendulum from swing up to stand up)

    JSME International Journal

    (1997)
  • K. Yoshida et al.

    Intelligent control using cubic neural network

    JSME International Journal

    (2000)
  • M. Takahashi, T. Narukawa, Kazuo Yoshida, Intelligent control using destabilized and stabilized controllers for a swung...
There are more references available in the full text version of this article.

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Kazuo Yoshida received B.E. and M.E. degrees in the Department of System Design Engineering from Keio University in 1973 and 1975, respectively. He received the Dr. Eng. degree from Keio University, Yokohama, Japan, in 1978. In 1981, he started working as a Research Assistant of the Department of Mechanical Engineering, Keio University, Yokohama, Japan, where he became an Associate Professor in 1984 and a Professor in 1994. From 1996 to 2008, he was a Professor at the Department of System Design Engineering, Keio University and from 2001 to 2008, he was a Vice-President of Keio University. From 2003 to 2007, he was a Leader of the 21st Century COE Program: “System Design: Paradigm shift from Intelligence to Life”. His primary research interests included control engineering, motion and vibration control, design and dynamics. He was a principal figure worldwide in autonomous robotics research. He designed and built a variety of intelligent robots, obtaining many important results such as winning three times the world championship in the middle-size robot league in the international RoboCup competition. He died in March 2008, at the age of 58 years.

1

Prof. Kazuo Yoshida died in March 2008. This paper was originally presented by himself during the “Symposium on Creation of a New AI System Based on the Integration of Logic and Psychology”, organized at Keio University, Yokohama (Japan), in March 2005.

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