ニューラルネットワークの解析的表現に基づく身体表現の獲得と利用

抄録

Body representation is one of bases of adaptive human behavior, e.g., postural and motion control, tool use, imitation and self-recognition. However, it is still difficult to understand how we acquire and apply it to such behavior. Here, we propose a novel approach to explain the mechanism of acquisition and application of body representation from the control engineering viewpoint, based on analytical expression of neural networks which approximate forward dynamics. In this paper, it was suggested by simulating 2-link planar manipulator control in various situation, that body representation acquired through the proposed method had plasticity and was able to be applied to manipulator control, state estimation and prediction.