〇劉海龍，谷口忠大， ガウス過程状態空間モデルを用いた人間ロボット間インタラクションの構成 第57回システム制御情報学会研究発表講演会(SCI13),CD-111-2, (2013.5.15-17@神戸)

发布日期：Oct 01, 2013 2:57:6 PM

Abstract:

In this paper, we proposed a machine learning method which realizes human-robot interaction without pattern recognition. In most previous researches, action patterns were recognized as discrete states, e.g., “kick”, “punch” or “jump”. Discrete states are a kind of low-dimensional representation of movements. In this work, we try to realize human-robot interaction without performing pattern recognition. In particular, we use Gaussian process latent variable model to acquire a nonlinear low-dimensional state representation. As an example, we developed a robot which plays paper-stone-scissors with a human player.