Name
Abstract | ||
|---|---|---|
An important function missing from current robotic systems is a human-like method for creating behavior from symbolized information. This function could be used to assess the extent to which robotic behavior is human-like because it distinguishes human motion from that of human-made machines created using currently available techniques. The purpose of this research is to clarify the mechanisms that generate automatic motor commands to achieve symbolized behavior. We design a controller with a learning method called tacit learning, which considers system-environment interactions, and a transfer method called mechanical resonance mode, which transfers the control signals into a mechanical resonance mode space (MRM-space). We conduct simulations and experiments that involve standing balance control against disturbances with a two-degree-of-freedom inverted pendulum and bipedal walking control with humanoid robots. In the simulations and experiments on standing balance control, the pendulum can become upright after a disturbance by adjusting a few signals in MRM-space with tacit learning. In the simulations and experiments on bipedal walking control, the robots realize a wide variety of walking by manually adjusting a few signals in MRM-space. The results show that transferring the signals to an appropriate control space is the key process for reducing the complexity of the signals from the environment and achieving diverse behavior. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3389/fnbot.2018.00043 | FRONTIERS IN NEUROROBOTICS |
Keywords | Field | DocType |
mechanical resonance mode,tacit learning,control structure,symbolized information,human-like movement | Control theory,Inverted pendulum,Computer science,Control engineering,Human motion,Standing balance,Mechanical resonance,Artificial intelligence,Robot,Pendulum,Machine learning,Humanoid robot | Journal |
Volume | ISSN | Citations |
12 | 1662-5218 | 0 |
PageRank | References | Authors |
0.34 | 12 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shotaro Okajima | 1 | 0 | 1.35 |
| Maxime Tournier | 2 | 0 | 0.34 |
| Fady Alnajjar | 3 | 66 | 12.23 |
| Mitsuhiro Hayashibe | 4 | 190 | 33.44 |
| Yasuhisa Hasegawa | 5 | 456 | 94.62 |
| Shingo Shimoda | 6 | 135 | 20.49 |