Learning and Dynamic Control of Robot
Grant-in-Aid for Scientific Research (C)
|Allocation Type||Single-year Grants|
|Research Institution||The University of Tokyo|
OKABE Yoichi The University of Tokyo, RCAST, Professor, 先端科学技術研究センター, 教授 (50011169)
KITAGAWA Manabu The University of Tokyo, RCAST, Research Associate, 先端科学技術研究センター, 助手 (30110711)
|Project Period (FY)
1998 – 1999
Completed(Fiscal Year 1999)
|Budget Amount *help
¥4,000,000 (Direct Cost : ¥4,000,000)
Fiscal Year 1999 : ¥1,100,000 (Direct Cost : ¥1,100,000)
Fiscal Year 1998 : ¥2,900,000 (Direct Cost : ¥2,900,000)
|Keywords||LEARNING / CONTROL / ROBOT / OSCILLATION / NEURAL NETWORKS / 周期運動 / ヘビロボット / 歩行ロボット / モデレーティズム / リカレント|
The real motion of creature is dynamic and hard to analyze. The purpose of this research is to make a robot acquire the motion by learning.
We made several robots, and they acquire giant swing motion of horizontal bar, hopping motion by one leg, two-foot walking motion, and serpentine motion with four joints.
(1). Giant Swing Robot
Giant swing robot is a double-pendulum hanged on a horizontal bar. In this robot, there is a DC-motor at a joint between the pendulums, and are angle sensors at every joint. We tried to find the way to control the giant swing motion by changing the torque of DC-motor. We succeeded to execute the sequential giant swing motion, by using the control based on simple rule base.
(2). Hopping Robot
Hopping robot has a leg that swings back and forth. The power, which swings the lag, is given by DC-motor. We tried to find the way to control the hopping motion by changing the torque of DC-motor, in the similar way of 1. We succeeded to execute the sequential hopping motion.
(3). Two-foot Robot
Two-foot walking is a typical motion of human beings. We made a two-foot robot with four servomotors and tried to control the walking motion with neural oscillator networks. As a result, we succeeded to execute stabilized walking motion.
(4). Four-joint Robot
To the next step, we made four-joint robot with four servomotors at every joint. We tried to let the robot get efficient serpentine motion by learning, using control system with neural oscillator networks. We succeeded to execute efficient serpentine motion by learning.
For future works, we are thinking to make the hopping robot to achieve the hopping motion by learning.
Moreover, as development of those researches, we are thinking to control hopping motion and two-feet walking motion by using neural network.
Research Output (13results)