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We propose a practical state-of-the-art method to develop a machine-learning-based humanoid robot that can work as a production line worker. The proposed approach provides an intuitive way to collect data and exhibits the following characteristics: task performing capability, task reiteration ability, generalizability, and easy applicability. The proposed approach utilizes a real-time user interface...
Human communicative behavior is both dynamic and bidirectional. This study aims to analyze such behavior by conducting imitative interactions between human subjects and a humanoid robot that has a neuro-dynamical system. For this purpose, we take a robot-centered approach in which the change in robot performance according to difference in human partner is analyzed, rather than adopting the typical...
The recovery of motor function after stroke is widely considered to result from brain plasticity. However, what kind of training exercise can better provoke brain plastic processes is still unclear. Studying regional brain activation during a specific training exercise may provide value information that can help design more effective therapeutic approaches. In this paper, we monitored brain activation...
This paper investigates the essential difference between two types of behavior generation schemes, namely, sensory reflex behavior generation and intentional proactive behavior generation, by proposing a dynamic neural network model referred to as stochastic multiple-timescale recurrent neural network (S-MTRNN). The proposed model was employed in an experiment involving robots learning to cooperate...
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