An intelligent robot with learning and adaptive functions based on multi-layered structure of knowledge
Tomohiko Sato, Toru Yamaguchi, Michihiro Yoshihara · IEEJ Transactions on Electronics Information and Systems · 1996
This paper proposes an intuition-based agent model in an Intelligent Industrial System(IIS). This is a model of an agent that cooperates human beings or the outside world. It has three-layered structure of knowledge. The upper layer has abstract knowledge as macro level. The middle one has concrete knowledge as micro level. The lower one has a local feed back, which consists of a feature extractor and action generator, by which communicates the outside world. The model has three functions since it is easy to recognize all knowledge in the model and the model processes knowledge top-down and bottom-up between the upper and the middle layer. (1) An interface function that communicates human beings or the outside world using images and sounds. (2) A learning function using function (1). (3) An adaptive function that corresponds to environmental changes using creativity. Then, this paper shows the following two experimental systems to achieve the above functions. (a) A gesture instruction learning system in which a mobile robot learns a trajectory using the qualitative sense inherent in a human macro qualitative instruction. (b) A self-organizing system based on chaotic dynamics in which a mobile robot creates a new knowledge adapted to an environmental change and learn one autonomously. Some experimental results show the effectiveness of the agent model.