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Postural stabilization of flexible robot by motor learning

The flexible robot introduced as above is suitable for physical contact with humans while it is difficult to stabilize its posture. Because of its complex time-space dynamics, traditional model-based control methods are not effective for the robots with large number of flexible joints. Therefore, motor learning methods, in which robots learn the way to control their body through motor experience like humans, is the main methodology to stabilize the developed robot in my project.

Equilibrium model learning

A joint research with a group at Bielefeld University in Germany has been started to test their motor learning methods (Equilibrium model learning and Rapid mapping learning between motor space and posture space) on my robot. One Ph.D. candidate student from the university is staying our laboratory and testing the above method. Although the progress is delayed about a half year due to the schedule change of his stay, the initial progress is going well.

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