Abstract
Reliable predictability, which is tightly connected to consistency of environmental changes, is one of the main factors that determine human behaviors. As a constructive approach to understanding this mechanism, the authors have developed a method to generate autonomous object pushing motions based on consistency of object motions using a humanoid robot. The method consists of constructing a dynamics prediction model using Recurrent Neural Network with Parametric Bias (RNNPB), and motion searching based on an object consistency evaluation function using Steepest Descent Method. The model was analyzed through two experiments, pushing cylindrical objects with a humanoid robot. The analysis has shown the method's effectivity and limitations to generate consistent object motions.
