| Budget Amount *help |
¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Fiscal Year 2012: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2011: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Research Abstract |
In this research, we realized autonomous extraction of object recognition features and tool using motion generation based on object manipulation task of a robot. A recurrent neural network was utilized as the robot’s body model to learn the robot’s motions and the environmental change. During tool using experiments, the robot was capable of identifying the untrained L-shaped tool based on experiences with T- and I-shaped tools, to generate pulling motions for a target object.
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