Ryunosuke Yokoya

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— Robot imitation is a useful and promising alternative to robot programming. Robot imitation involves two crucial issues. The first is how a robot can imitate a human whose physical structure and properties differ greatly from its own. The second is how the robot can generate various motions from finite programmable patterns (generalization). This paper(More)
— This paper proposes a novel model which enables a humanoid robot infant to discover other individual (e.g. human parent). In this work, the authors define " other individual " as an actor which can be predicted by a self-model. For modeling the developmental process of discovering ability, the following three approaches are employed. (i) Projection of a(More)
— Consistency of object dynamics, which is related to reliable predictability, is an important factor for generating object manipulation motions. This paper proposes a technique to generate autonomous motions based on consistency of object dynamics. The technique resolves two issues: construction of an object dynamics prediction model and evaluation of(More)
This paper proposes a model that enables a robot to predict and imitate the motions of another by reusing its body forward-inverse model. Our model includes three approaches: (i) projection of a self-forward model for predicting phenomena in the external environment (other individuals), (ii) " triadic relation " that is mediation by a physical object(More)
Catadioptric imaging systems use curved mirrors to capture wide fields of view. However, due to the curvature of the mirror, these systems tend to have very limited depth of field (DOF), with the point spread function (PSF) varying dramatically over the field of view and as a function of scene depth. In recent years, focal sweep has been used extensively to(More)
— This paper presents a method to autonomously extract object features that describe their dynamics from active sensing experiences. The model is composed of a dynamics learning module and a feature extraction module. Recurrent Neural Network with Parametric Bias (RNNPB) is utilized for the dynamics learning module, learning and self-organizing the(More)
— This paper proposes a novel method which enables a humanoid robot acquires an ability for imitation focusing on the developmental process of human infants. In this work, the robot infant predicts a human parent's motions by reusing its own self-model. For the self-model of a robot, we applied a recurrent neural network with parametric bias (RNNPB) model(More)
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