| Project/Area Number |
12650442
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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 |
Control engineering
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| Research Institution | Nagoya University |
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Principal Investigator |
ISHIGURO Akio Nagoya University Dept. of Computational Science and Engineering Associate Professor, 大学院・工学研究科, 助教授 (90232280)
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| Project Period (FY) |
2000 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥2,900,000 (Direct Cost: ¥2,900,000)
Fiscal Year 2001: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | Evolutionary Robotics / Neural Networks / Neuromodulation / Neuromodulators / Real-time Adaptation / Autonomous Mobile Robots / Locomotion Control / Central Pattern Generators / 適応能力 / 自律律移動ロボット / 拡散・反応 / 身体性 |
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| Research Abstract |
Recently the Evolutionary Robotics (ER) approach has been attracting a lot of concern in the field of robotics and artificial life. In contrast to the conventional approaches where designers have to construct controllers in a top-down manner, the methods employed in the ER approach have significant advantages since they can autonomously and efficiently construct controllers by taking embodiment (e.g. mechanical dynamics, physical size and shape of robots, sensor/motor properties and disposition etc.) and the interaction dynamics between the robot and its environment into account.
In light of these facts, in this research project, an evolutionary creation of adaptive neurocontrollers has been investigated. To this end, the concept of neuromodulation, allowing to evolve neural networks which can adjust not only the synaptic weights but also the structure of the neural network by blocking and/or activating synapses or neurons according to the current situation has been introduced. This idea has been applied to the control of a peg-pushing robot and a legged robot, which is intrinsically unstable. Simulations have been conducted and the results have showed that this approach is remarkably promising.
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