| Co-Investigator(Kenkyū-buntansha) |
YAMANE Katsu The University of Tokyo, Graduate School of Information Science and Technology, Associate Professor (00361543)
SUGIHARA Tomomichi The University of Tokyo, Graduate School of Information Science and Technology, Assistant Professor (70422409)
OKADA Masafumi Tokyo Institute of Technology, Graduate School of Science and Engineering, Associate Professor (60323523)
SEKIGUCHI Akinori Hirosaki University, Faculty of Science and Engineering, Assistant Professor (80344612)
大武 美保子 東京大学, 大学院・情報理工学系研究科, 研究拠点形成特任教員 (10361544)
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| Budget Amount *help |
¥122,070,000 (Direct Cost: ¥93,900,000、Indirect Cost: ¥28,170,000)
Fiscal Year 2007: ¥18,200,000 (Direct Cost: ¥14,000,000、Indirect Cost: ¥4,200,000)
Fiscal Year 2006: ¥18,200,000 (Direct Cost: ¥14,000,000、Indirect Cost: ¥4,200,000)
Fiscal Year 2005: ¥30,290,000 (Direct Cost: ¥23,300,000、Indirect Cost: ¥6,990,000)
Fiscal Year 2004: ¥36,270,000 (Direct Cost: ¥27,900,000、Indirect Cost: ¥8,370,000)
Fiscal Year 2003: ¥19,110,000 (Direct Cost: ¥14,700,000、Indirect Cost: ¥4,410,000)
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| Research Abstract |
1. Dynamical Information Processing Theory We have established two methods for designing dynamical information processing mechanisms based on polynomials and physical dynamics systems. We also introduced a parameter representing the plasticity of dynamical systems and developed learning and development model based on the plasticity. A communication model was realized utilizing the attractors of the dynamical system.
2. Mathematical Model of Mirror Neurons We established a mathematical model and its computational algorithms for modeling mirror neurons using Hidden Markov Models (HMM). Based on hierarchical HMMs, we realized the abstract ion of behaviors. We also combined the hierarchical mirror neuron model with language analysis system equipped with a common sense database.
3. Experimental Study on Perception and Generation of Behaviors through Humanoid Robots We designed and built a humanoid robot that moves in accordance with the gravity. We also developed a method for acquiring motion patterns and controllers by measuring human motions. Finally, we performed several experiments combining the humanoid robot with the dynamical information processing system, language analysis system, and behavior perception and generation system.
4. Simulation of Large-Scale Sensor-Motor System through Detailed Human Musculo-Skeletal Models We developed algorithms for estimating the muscle tensions and simulation human motions based on motion capture data. We accelerated the algorithms for detailed human model by employing parallel processing. A large-scale model was developed for simulating the sensor-motor system of the human body and combined with the dynamical information processing system.
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