Control of Mechanical System with Knowledge Data Base
Project/Area Number |
62420028
|
Research Category |
Grant-in-Aid for General Scientific Research (A)
|
Allocation Type | Single-year Grants |
Research Field |
機械力学・制御工学
|
Research Institution | The University of Tokyo |
Principal Investigator |
MIURA Hirofumi The University of Tokyo, Mechanical Eng., Professor, 工学部, 教授 (50010682)
|
Co-Investigator(Kenkyū-buntansha) |
SHIMOYAMA Isao The University of Tokyo, Mechanical Eng., Associate Professor, 工学部, 助教授 (60154332)
|
Project Period (FY) |
1987 – 1989
|
Project Status |
Completed (Fiscal Year 1989)
|
Budget Amount *help |
¥19,200,000 (Direct Cost: ¥19,200,000)
Fiscal Year 1989: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 1988: ¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 1987: ¥14,700,000 (Direct Cost: ¥14,700,000)
|
Keywords | Intelligent Robot / Intelligent Traveling / Learning Ability / Knowledge Data Base / 知識デ-タベ-ス / 知識データベース |
Research Abstract |
In this research, two kinds of mechanical system have been treated. The results are described in the following. (1) Intelligent Mobile Mechanical System-The quadruped robots were constructed. They walked autonomously. In walking motion, there are so many parameters and the criteria function for deciding a good walking pattern is not known. We investigated and analyzed the walking motion of actual animals ( dogs were mainly investigated ) in detail. It was found that energy consumption is one of very important parameters for walking motion. Gait ( which legs swing in which order ), duty factor ( ratio of the time the leg is contacting the floor over one cycle of walk ) and other parameters are decided by the criteria to minimize the energy consumption. This was concluded by comparison of investigating results of actual animals and results of dynamic analysis of the model. By control algorithm using this knowledge, the quadrupeds walked very smoothly in stable state. (2) Software for Intelligent Robot-We succeeded in constructing the robot having problem solving ability and learning ability. Problem solving means planning of action and execution of it. Learning means obtaining of necessary knowledges for problem solving. Robots which work in the real world have two problems. They are uncertainty of the result of action and lack of knowledge about working objects and environment. To conquer these problem, ability of problem solving and ability of learning requested. In this research, these two abilities were studied together. The results have been highly evaluated internationally.
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Report
(4 results)
Research Products
(25 results)