| Project/Area Number |
18560243
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent mechanics/Mechanical systems
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
IWATSUKI Nobuyuki Tokyo Institute of Technology, Graduate School of Engineering, Professor (70193753)
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| Co-Investigator(Kenkyū-buntansha) |
MORIKAWA Koichi Tokyo Institute of Technology, Graduate School of Engineering, Assistant Professor (00282830)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,830,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥330,000)
Fiscal Year 2007: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2006: ¥2,400,000 (Direct Cost: ¥2,400,000)
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| Keywords | Hyper Redundant Robot / Learning Control / Dexterous Machinery / Cooperative Motion / Intelligent Systems / Robotic Manipulator / Motion Control / Trajectory Generation / 運動学 |
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| Research Abstract |
Aiming to establish effective motion control scheme for hyper redundant robot by learning control based on linear combination of error history, new methods to set suitable subtasks and to obtain suitable initial configuration of the robots, the optimum motion control based on dexterity of the robots, and flexibility control of the robots with elastic elements are discussed. The obtained results are summarized as follows :
(1)For hyper redundant planar serial manipulators, new methods to set subtask so as to pass obstacles away or assist main task were proposed and formulated.
(2) A new 'Backward learning scheme', in which a converged configuration obtained with forward learning was set as initial configuration and the learning processes were repeated, was proposed so as to obtain suitable initial configuration.
(3)Quantitative indices to evaluate assistability for main task and movability of links were derived from column vector of Jacobian matrices of joints. By setting the indices as objective functions, the joint inputs were optimized with gradient projection method and learning control.
(4) new flexibility control method to specify both of output displacement and stiffness distribution of a closed-loop redundant manipulator with elastic passive joints was formulated and was experimentally examined. A prototype can then manipulate soft/hard objects while controlling output flexibility.
It was thus revealed that the learning control based on linear combination of error history could realize motion and output force control while utilizing redundancy.
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