対象物の形状に合わせて手の形を決定する神経回路モデル

DOI Web Site 被引用文献10件 参考文献14件

書誌事項

タイトル別名
  • A Neural Network Models that Designs Hand Shapes to Grasp Objects
  • タイショウブツ ノ ケイジョウ ニ アワセテ テ ノ カタチ オ ケッテイスル

この論文をさがす

抄録

From the viewpoint of computational theory, we discuss the visuomotor transformation in human grasping movements. Determining a hand shape to grasp an object is an ill-posed problem, because there are many ways to grasp the object. We propose two kinds of neural network architectures for calculating the optimal hand shape. Network operation is divided into a learning phase and an optimization phase. In the learning phase, an internal model that represents the relation between objects and hand shapes is acquired. In the optimization phase, the most suitable hand shapes for grasping objects are designed by using a relaxation computation of the network. In the first model, the internal representations of objects are specified with symbolic or population coding. In the second model, no representation of objects is defined beforehand; instead, the neural network acquires the internal representations of objects by integrating visual and motor information.

収録刊行物

被引用文献 (10)*注記

もっと見る

参考文献 (14)*注記

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ