Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Tool-Body Assimilation Model Based on Body Babbling and a Neuro-Dynamical System for Motion Generation
verfasst von : Kuniyuki Takahashi, Tetsuya Ogata, Hadi Tjandra, Shingo Murata, Hiroaki Arie, Shigeki Sugano
Erschienen in: Artificial Neural Networks and Machine Learning – ICANN 2014
Verlag: Springer International Publishing
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We propose a model for robots to use tools without predetermined parameters based on a human cognitive model. Almost all existing studies of robot using tool require predetermined motions and tool features, so the motion patterns are limited and the robots cannot use new tools. Other studies use a full search for new tools; however, this entails an enormous number of calculations. We built a model for tool use based on the phenomenon of tool-body assimilation using the following approach: We used a humanoid robot model to generate random motion, based on human body babbling. These rich motion experiences were then used to train a recurrent neural network for modeling a body image. Tool features were self-organized in the parametric bias modulating the body image according to the used tool. Finally, we designed the neural network for the robot to generate motion only from the target image.