| Project/Area Number |
05505002
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| Research Category |
Grant-in-Aid for Developmental Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
機械工作・生産工学
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| Research Institution | Osaka University |
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Principal Investigator |
IWATA Kazuaki Osaka Univ. Faculty of Engineering Professor, 工学部, 教授 (30031066)
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| Co-Investigator(Kenkyū-buntansha) |
OSHIMA Michitaka Mitsubishi Electric Co.Ltd Associate section chief, 産業システム研究所, 課長
HIRAI Shinichi Osaka Univ. Faculty of Engineering Research Associate, 工学部, 助手 (90212167)
ONOSATO Masahiko Osaka Univ. Faculty of Engineering Assistant Professor, 工学部, 助教授 (80177279)
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| Project Period (FY) |
1993 – 1994
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| Project Status |
Completed (Fiscal Year 1994)
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| Budget Amount *help |
¥28,500,000 (Direct Cost: ¥28,500,000)
Fiscal Year 1994: ¥9,000,000 (Direct Cost: ¥9,000,000)
Fiscal Year 1993: ¥19,500,000 (Direct Cost: ¥19,500,000)
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| Keywords | proficient / expert model / process model / learning / memory-based learning / skill / experience / model-based control |
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| Research Abstract |
In this report, scraping operation is firstly analyzed in order to investigate the proficient process of human. The scraping is a process to generate flat surfaces from roughly cut surfaces. It is found that the proficiency of the scraping consists of the understanding of surface shpes, planning scraping sequences, and the removal of unnecessary parts.
Second, a prototype of a proficient machine tool is developed. The proficient machine tool can design machining process via process simulation and can update the process model through actual machining. Namely, it has a capability of learing from operation experience. In the learning, a desirable process model is selected among multiple process models via process simulation. After actual milling, new process model parameters are derived from measured sensor signals using a mathematical programming method. The process model correponding to current conditions is adjusted and is memorized by use of a memory-based learning. It is found that prediction correctness of the process simulation can be improved as the machine tool obtains much experience of the machining.
Third, a prototype of a proficient manipulator is developed. It is consists of a sensor-feedback manipulator, a device capable of measuring human skillful motion, and a workstation for operation model construction and operation planning. Transplanting human skillful motion to a manipulator is examined. Human action during the insertion of a deformable hose into a plug is measured by use of the position and the force sensors, and analyzed with regard to the contact between the hose and the plug. It is found that the pull motion during the process is effective for the successful insertion of a deformable hose into a plug. Embedding effective pull motion in a manipulator program, it turns out that the manipulator can perform the insertion successfully.
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