Realization of the human skill in the peg-in-hole task using hybrid architecture

Since impedance control can achieve the desired dynamics between tool and environment, it is widely used for complex tasks. But deciding the impedance parameters for the task is very difficult because they cannot be calculated analytically. If we can extract impedance parameters from human demonstration, it is appropriate to use them. However, if there exist disturbances and/or noise at the playback stage, which was not taken into account at the skill acquisition stage, the executed task by the robot is far different from the human demonstration. In order to realize the robust skill, we introduce a hybrid architecture. This architecture enables robots to use the most suitable dynamics (impedance parameters) for each task situation. Moreover, because of event driven architecture, we can expect the improvement of robustness of the skill in the time domain. We apply our proposed method to the peg-in-hole task, and show some experimental results