Paper

[1] Arbib, M. A., Oztop, E., & Zukow-Goldring, P. (2005) Language and the mirror system: A percepton/action based approach to communicative development. Cognitie, Creier, Comportament, IX(3):239-272.

[2] Bentivegna, D. C., Atkeson, C. G., & Cheng, G. (2004) Learning tasks from observation and practice. Robotics and Autonomous Systems, 47:163-169.

[3] Bentivegna, D. C., Atkeson, C. G., Ude, A., & Cheng, G. (2004) Learning to act from observation and practice. International Journal of Humanoid Robotics, 1(4):585-611.

[4] Billard, A., Epars, Y., Calinon, S., Schaal, S., & Cheng, G. (2004) Discovering optimal imitation strategies. Robotics and Autonomous Systems, 47:69-77.

[5] Chaminade, T., Hodings, J., & Kawato, M. (2007) Anthropomorphism influences perception of computer-animated characters' actions. Social, Cognitive and Affective Neuroscience, 2(3):206-216.

[6] Chaminade, T., Oztop, E., Cheng, G., & Kawato, M. (2008) From self-observation to imitation: Visuomotor association on a robotic hand. Brain Research Bulletin, 75:775-784.

[7] Cheng, G., Hyon, S., Morimoto, J., Ude, A., Hale, J. G., Colvin, G., Scroggin, W., & Jacobsen, S. C. (2007) CB: A humanoid research platform for exploring neuroscience. Advanced Robotics, 21:1097-1114.

[8] Endo, G., Morimoto, J., Matsubara, T., Nakanishi, J., & Cheng, G. (2006) Learning CPG-based biped locomotion with a policy gradient method: Application to a humanoid robot. The International Journal of Robotics Research, 27(2):213-228.

[9] Gaskett, C., Ude, A., & Cheng, G. (2005) Hand-eye coordination through endpoint closed-loop and learned endpoint open-loop visual servo control. International Journal of Humanoid Robotics, 2(2):203-224.

[10] Hale, J. G., Hohl, B., Hyon, S., Matsubara, T., Moraud, E. M., & Cheng, G. (2008) Highly precise dynamic simulation environment for humanoid robots. Advanced Robotics, 22(10):1075-1105.

[11] Hale, J. G., & Pollick, F. E. (2005) "Sticky hands": Learning and generalisation for cooperative physical interactions with a humanoid robot. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 35(4):512-521.

[12] Hyon, S. (2009) Compliant terrain adaptation for biped humanoids without measuring ground surface and contact forces. IEEE Transactions on Robotics, 25(1):171-178.

[13] Hyon, S., Hale, J. G., & Cheng, G. (2007) Full-body compliant human-humanoid interaction: Balancing in the presence of unknown external forces. IEEE Transactions on Robotics, 23(5):884-898.

[14] Hyon, S. (2009) A motor control strategy with virtual musculoskeletal systems for compliant anthoropomorphic robots. IEEE/ASME Transactions Mechatronics, 14(6):677-688.

[15] Matsubara, T., Morimoto, J., Nakanishi, J., Hyon, S., Hale, J. G., & Cheng, G. (2008) Learning to acquire whole-body humanoid center of mass movements to achieve dynamic tasks. Advanced Robotics, 22(10):1125-1142.

[16] Matsubara, T., Morimoto, J., Nakanishi, J., Sato, M., & Doya, K. (2006) Learning CPG-based biped locomotion with a policy gradient method. Robotics and Autonomous Systems, 54:911-920.

[17] Miyamoto, H., Morimoto, J., Doya, K., & Kawato, M. (2004) Reinforcement learning with via-point representation. Neural Networks, 17:299-305.

[18] Moren, J., Ude, A., Koene, A., & Cheng, G. (2008) Biologically based top-down attention modulation for humanoid interactions. International Journal of Humanoid Robotics, 5(1):3-24.

[19] Morimoto, J., & Atkeson, C. G. (2007) Learning biped locomotion: Application of poincare-map-based reinforcement learning. IEEE Robotics and Automation Magazine, 14:41-51.

[20] Morimoto, J., & Atkeson, C. G. (2009) Nonparametric representation of an approximated poincare map for learning biped locomotion. Autonomous Robots, 27(2):131-144.

[21] Morimoto, J., & Doya, K. (2005) Robust reinforcement learning. Neural Computation, 17:335-359.

[22] Morimoto, J., & Doya, K. (2007) Reinforcement learning state estimator. Neural Computation, 19(3):730-756.

[23] Morimoto, J., Endo, G., Nakanishi, J., & Cheng, G. (2008) A biologically inspired biped locomotion strategy for humanoid robots: Modulation of sinusoidal patterns by a coupled oscillator model. IEEE Transactions on Robotics, 24(1):185-191.

[24] Nakanishi, J., Cory, R., Mistry, M., Peters, J., & Schaal, S. (2008) Operational space control: A theoretical and empirical comparison. International Journal of Robotics Research, 27(6):737-757.

[25] Nakanishi, J., Farrell, J. A., & Schaal, S. (2005) Composite adaptive control with locally weighted statistical learning. Neural Networks, 18:71-90.

[26] Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., & Kawato, M. (2004) Learning from demonstration and adaptation of biped locomotion. Robotics and Autonomous Systems, 47:79-91.

[27] Nakanishi, J., & Schaal, S. (2004) Feedback error learning and nonlinear adaptive control. Neural Networks, 17(10):1453-1465.

[28] Oztop, E. (2006) An upper bound on the minimum number of monomials required to separate dichotomies of {-1,1}n. Neural Computation, 18:3119-3138.

[29] Oztop, E., Bradley, N. S., & Arbib, M. A. (2004) Infant grasp learning: a computational model. Experimental Brain Research, 158:480-503.

[30] Oztop, E., Franklin, D. W., Chaminade, T., & Cheng, G. (2005) Human-humanoid interaction: Is a humanoid robot perceived as a human? . International Journal of Humanoid Robotics, 2(4):537-559.

[31] Oztop, E., Imamizu, H., Cheng, G., & Kawato, M. (2006) A computational model of anterior intraparietal (AIP) neurons. Neurocomputing, 69:1354-1361.

[32] Oztop, E., Wolpert, D., & Kawato, M. (2005) Mental state inference using visual control parameters. Cognitive Brain Research, 22:129-151.

[33] Oztop, E. (2009) Sign representation of boolean functions using a small number of monomials. Neural Networks, 22(7):938-948.

[34] Peters, J., Mistry, M., Udwadia, F., Nakanishi, J., & Schaal, S. (2008) A unifying framework for robot control with redundant DOF's. Autonomous Robots, 24:1-12.

[35] Pollick, F. E., Hale, J. G., & Tzoneva, M. (2005) Perception of humanoid movement. International Journal of Humanoid Robotics, 2(3):277-300.

[36] Ude, A., Omrcen, D., & Cheng, G. (2008) Making object learning and recognition an active process. International Journal of Humanoid Robotics, 5(2):267-286.

Paper

[1] 丸山淳一, 松原崇光, Hale, J. G., 森本淳 (2009) 強化学習を用いたヒューマノイドロボットによる転倒回避ステップ動作の学習. 日本ロボット学会誌, 27(5):527-537.

[2] 玄相昊, 藤本健治 (2008) ハミルトン力学系の対称軌道族と２足歩行の大域的歩容生成への応用. 日本ロボット学会誌, 26(4):72-80.

[3] 佐藤訓志, 藤本健治, 玄相昊 (2008) ハミルトン系の変分対称性に基づく１脚ロボットの最適歩容生成. 計測自動制御学会論文集, 43(12):1103-1110.

[4] 松原崇充, 森本淳, 中西淳, 佐藤雅昭, 銅谷賢治 (2005) 方策こう配法を用いた動的行動則の獲得：2足歩行運動への適用. 電子情報通信学会論文誌, J88-D-II(1):53-65.

[5] 有木由香, 森本淳, 玄相昊 (2008) 動作認識における床反力情報の推定と見まね学習への適用. 電子情報通信学会誌 論文誌D, J91-D(9):2394-2403.

[6] 玄相昊 (2009) 複数の接地部分と冗長関節を有するヒューマノイドロボットの受動性に基づく最適接触力制御. 日本ロボット学会誌, 27(2):178-187.

[7] 玄相昊 (2009) 準静的に獲得した関節軌道を利用して動的な類似運動を逐次的に学習する方法. 日本ロボット学会誌, 27(9):1025-1028.

Review paper, Book chapter

[1] Bentivegna, D. C., Atkeson, C. G., & Cheng, G. (2007) Challenges and issues faced in building a framework for conducting research in learning from observation. In Dautenhahn, C. L. N. a. K., (Ed.) In Imitation and social learning in robots, humans and animals behavioural, social and communication dimensions, pp. 47-66, Cambridge University Press, Cambridge.

[2] Cheng, G., Metta, G., & Sandini, G. (2008) Humanoid technologies: "Know-how". In Robotics and Autonomous Systems, vol. 56, pp. 1-3.

[3] Cheng, G., Schaal, S., & Atkeson, C. G. (2005) Editorial. In International Journal of Humanoid Robotics, vol. 2 (4), pp. 389-390, World Scientific Publishing Company.

[4] Gurbuz, S., Inoue, N., & Cheng, G. (2007) Real-time vision based mouth tracking and parameterization for a humanoid imitation task. In Filho, A. C. d. P., (Ed.) In Humanoid robots new developments, pp. 241-252, I-Tech Education and Publishing, Vienna.

[5] Hale, J. G. (2005) Practical and theoretical research into humanoid motion and interaction. In IEEE System, Man, and Cybernetics Society eNewsletter.

[6] Hale, J. G., & Pollick, F. E. (2007) Sticky hands. In Filho, A. C. d. P., (Ed.) In Humanoid robots new developments, pp. 265-284, I-Tech Education and Publishing, Vienna.

[7] Kawato, M. (2008) Brain controlled robots. In Falaschi, A., ICGEB, T., & SNS, P., (Eds.), In HFSP Journal, vol. 2, pp. 136-142.

[8] Kawato, M. (2008) From "understanding the brain by creating the brain" towards manipulative neuroscience. In Yanagida, T., Okano, H., & Iriki, A., (Eds.), In Philosophical Transactions B, vol. 363, pp. 2201-2214, THE ROYAL SOCIETY.

[9] Oztop, E. (2007) Models of mirror system. In Scholarpedia, vol. 2 (10), p. 3276.

[10] Oztop, E., Arbib, M. A., & Bradley, N. S. (2006) The development of grasping and the mirror system. In Arbib, M. A., (Ed.) In Action to language via the mirror neuron system, pp. 397-423, Cambridge University Press, Cambridge.

[11] Oztop, E., & Kawato, M. (2005) Conceptual and computational models of mirror neurons. 日本神経回路学会誌, vol. 12, pp. 61-73, 日本神経回路学会.

[12] Oztop, E., & Kawato, M. (2009) Models for the control of grasping. In Nowak, D. A., & Hermsdorfer, J., (Eds.), In Sensorimotor control of grasping physiology and pathophysiology, pp.110-124, Cambridge University Press, Cambridge.

[13] Oztop, E., Kawato, M., & Arbib, M. A. (2006) Mirror neurons and imitation: A computationally guided review. In Neural Networks, 2006/02 ed, vol. 19, pp. 254-271.

[14] Oztop, E. (2009) Mirror neurons: Extraordinary or ordinary? In Wang, W. S.Y., & Minett, J. W., (Eds.), In Language, Evolution, and the Brain, pp. 225-237, City University of Hong Kong Press, Hong Kong.

[15] Ude, A., Moren, J., & Cheng, G. (2007) Visual attention and distributed processing of visual information for the control of humanoid robots. In Hackel, M., (Ed.) In Humanoid robots human-like machines, pp. 423-236, I-Tech Education and Publishing, Vienna.

[16] 森本淳 (2008) 同期メカニズムを用いた二足歩行ー人間の歩行計測とヒューマノイドロボットの歩行制御ー. 日本ロボット学会誌, vol. 26, pp. 238-241, 日本ロボット学会, Tokyo, Japan.

[17] 中西淳, Ijspeer, A., Schaal, S., Cheng, G. (2004) 運動学習プリミティブを用いたロボットの見まね学習. 日本ロボット学会誌, vol. 22, pp. 176-181, 日本ロボット学会.

[18] 中西淳, Schaal, S. (2006) Feedback error learning and nonlinear adaptive control. 日本神経回路学会誌, vol. 13-1, pp. 37-38, 日本神経回路学会.

Invited talk

[1] Cheng, G. Paving the paths to the brain with humanoid robotics. Mechatronics & Robotics Conference 2004, Aachen, Germany 2004/09/16.

[2] Cheng, G. The computational brain project: Towards the realization of the computational brain, combining humanoid robotics and computational neuroscience. TUM Frontier Sciences at The University of Tokyo and Kyoto University---Tokyo Workshop 4, Humanoid Robots: Locomotion and Cognition, Tokyo, Japan 2005/10/05.

[3] Cheng, G. Paving the paths to the brain with humanoid robotics. IEEE International Conference on Robotics and Automation, Barcelona, Spain 2005/04/20.

[4] Cheng, G. Humanoid robotics perspectives to neuroscience. Bernstein Center for Computational Neuroscience Gottingen, Gottingen, Germany 2006/12/01.

[5] Cheng, G. Development of the JST-ICORP computational brain humanoid robot. ICORP Collaboration Workshop, Pittsburgh, PA, USA 2007/11/28.

[6] Cheng, G. Humanoid robotics perspectives to neuroscience. Vancouver Society for Cognitive Science Conference, Vancouver, Canada 2007/02/02-03.

[7] Cheng, G. Humanoid robotics perspectives to neuroscience. Second International Neuroscience Symposium of the IINN, Natal, Brazil 2007/02/23-25.

[8] Cheng, G. Towards the realisation of the computational brain with humanoid robots. Humanoids 2007 Workshop: Towards the Realisation of the Computational Brain with Humanoid Robots, Pittsburgh, PA, USA 2007/11/29.

[9] Hale, J. G. Simulation and control environment for humanoid robots. Humanoids 2007 Workshop: Towards the Realisation of the Computational Brain with Humanoid Robots, Pittsburgh, PA, USA 2007/11/29-12/01.

[10] Hale, J. G. Simulation and control environment for humanoid robots. ICORP Collaboration Workshop, Pittsburgh, PA, USA 2007/11/28.

[11] Kawato, M. Computational learning mechanisms for impedance control and internal model acquisition. The 31st NIPS International Symposium: Multidisciplinary Approaches to Sensorimotor Integration, Okazaki, Japan 2004/05/15-18.

[12] Kawato, M. Computational neuroscience and humanoid robotics Carnegie Mellon Robotics Institute 25th Anniversary "Robotics and Thought", Pittsburgh, PA, USA 2004/10/11-14.

[13] Kawato, M. Computational studies of temporal windows in cerebellar synaptic plasticity. OIST Initial Research Project Seminar, Okinawa, Japan 2004/06/18.

[14] Kawato, M. Computational-model-based imaging studies of decision learning. Tamagawa-COE International Symposium on Attention and Decision, Okazaki, Japan 2004/05/19-21.

[15] Kawato, M. MOSAIC: experimental supports and cognitive implications. International Workshop on Neural, computational and cognitive mechanisms of mentalizing, Kyoto, Japan 2004/05/05-07.

[16] Kawato, M. Positional variance of via-point trajectories; touchstone for two competing computational theories? Satellite workshop of Neuroscience 2004 "Advances in Computational Motor Control III", San Diego, USA 2004/10/22.

[17] Kawato, M. Robotics and the brain. Creating the Brain International Workshop, Saitama, Japan 2004/09/28.

[18] Kawato, M. Beyond Correlation - closing the loop between brain and theory by extracting representations and altered feedbacks. International Joint Conference on Neural Networks, Montreal, Canada 2005/07/31-08/04.

[19] Kawato, M. Connecting brain and humanoids by computational neuroscience. Robotics Science and Systems, Boston, USA 2005/06/08-10.

[20] Kawato, M. Connecting brain and robot by computational neuroscience. SICE Annual Conference, Okayama, Japan 2005/08/08-10.

[21] Kawato, M. Connecting brains and robots. ICORP LIVE 2005, Tokyo, Japan 2005/12/14.

[22] Kawato, M. Connecting brains and robots by computational theories. International Conference on Neural Networks and Brain, Beijing, China 2005/10/13-15.

[23] Kawato, M. Neuroscience and humanoid robots - hierarchical, modular reinforcement learning with MOSAIC. IEEE-RAS International Conference on Humanoid Robots, Ibaraki, Japan 2005/12/05-07.

[24] Kawato, M. Predictions by cerebellar internal models. Okinawa Computational Neuroscience Course, Okinawa, Japan 2005/07/01-10.

[25] Kawato, M. Toward computational manipulation of brain: brain network interface. International Symposium on The Art of Statistical Metaware, Tokyo, Japan 2005/03/14-16.

[26] Kawato, M. Connecting brains and robots. Japan-Canada Joint Workshop on Brain Science, Tokyo, Japan 2006/01/18.

[27] Kawato, M. Stability and plasticity dilemma from system biology point of view. HFSP Meeting 2006, Antwerp, Belgium 2006/06/01-02.

[28] Kawato, M. Towards manipulative neuroscience. 2006 Japan-Germany Symposium on Computational Neuroscience, Saitama, Japan 2006/02/01-04.

[29] Kawato, M. Towards manipulative neuroscience based on brain network interface. Bio-communication International Symposium 2006, Tokyo, Japan 2006/01/19.

[30] Kawato, M. Towards manipulative neuroscience based on brain network interface. Workshop on Brain Connectivity, Sendai, Japan 2006/05/17-20.

[31] Kawato, M. Towards manipulative neuroscience based on brain network interface. The first Symposium on Complex Medical Engineering, Kyoto, Japan 2006/05/17-20.

[32] Kawato, M. Towards manipulative neuroscience based on brain network interface. EPFL Seminar, Lausanne, Swiss 2006/05/30.

[33] Kawato, M. Towards manipulative neuroscience based on brain network interface. Neuroscience 2006, Kyoto, Japan 2006/07/19-21.

[34] Kawato, M. Towards manipulative neuroscience based on brain network interface. Brain-inspired Information Technology, Kyushu, Japan 2006/09/27-28.

[35] Kawato, M. Towards manipulative neuroscience based on brain-network-interface. 5th East Asian Biophysics Symposium & 44th Annual Meeting of the Biophysical Society of Japan, Okinawa, Japan 2006/11/12-16.

[36] Kawato, M. Towards manipulative neuroscience via brain-network-interface. CREST BMI workshop, Kyoto, Japan 2006/11/07-08.

[37] Kawato, M. Understanding brain by creating brain: from system biology of synaptic plasticity to humanoid robots. 20th International Congress of Biochemistry and Molecular Biology, Kyoto, Japan 2006/06/18-23.

[38] Kawato, M. Cerebellar long term depression as a supervised learning rule with all or nothing character at each synapse. 14th International Conference on Neural Information Processing, Fukuoka, Japan 2007/11/13-16.

[39] Kawato, M. Computational models of cerebellar motor learning and long-term depression. Tamagawa-Riken mini-Workshop on Integrative Brain Research, Tokyo, Japan 2007/08/04.

[40] Kawato, M. Exploring cause-and-effect proofs in system neuroscience utilizing brain network interfaces. KPUM Research & Development Seminar, Kyoto, Japan 2007/07/30.

[41] Kawato, M. Internal models and hierarchical reinforcement learning for social interaction. Tamagawa-Caltech Joint Workshop 2007 "Neural Mechanisms of the Social Mind", Tokyo, Japan 2007/12/06-08.

[42] Kawato, M. Manipulative neuroscience based on brain-network-interface. The Organization for Human Brain Mapping 2007, 13th Annual Meeting, Keynote Lecture, Chicago, USA 2007/06/10-14.

[43] Kawato, M. Towards manipulative neuroscience based on brain network interface. 10th Tamagawa-Riken Dynamic Brain Forum, Hakuba, Japan 2007/03/03-08.

[44] Kawato, M. Towards manipulative neuroscience based on brain network interface. RIKEN BSI Summer Program 2007, Wako, Japan 2007/07/23-08/03.

[45] Kawato, M. Towards manipulative neuroscience based on brain network interface. The 2007 USC Global Conference, Tokyo, Japan 2007/10/25-27.

[46] Kawato, M. Brain-controlled robots. Plenary Talk, 2008 IEEE International Conference on Robotics and Automation, Los Angeles, USA 2008/05/19-23.

[47] Kawato, M. Cerebellar long term depression as a supervised learning rule with all or nothing character. Computational and Systems Neuroscience 2008, Salt Lake City, USA 2008/02/28-03/02.

[48] Kawato, M. Computational model of transition from short to long-term memory in cerebellar LTD. The Uehara Memorial Foundation Symposium 2008, Tokyo, Japan 2008/06/30-07/02.

[49] Kawato, M. Internal models and hierarchical reinforcement learning for social interaction. International Conference of Cognitive Science, Seoul, Korea 2008/07/27-29.

[50] Kawato, M. Keynote talk "Computational advantages of internal models as self-consciousness". Association for the Scientific Study of Consciousness, Taipei, Taiwan 2008/06/19-22.

[51] Kawato, M. Towards manipulative neuroscience based on brain network interface. International Symposium on Hierarchy and Holism -Bridging Across Different Hierarchies in Natural Sciences-, Okazaki, Japan 2008/02/21-23.

[52] Kawato, M. Towards manipulative neuroscience based on brain network interface. University of Southern California Seminar 2008, Los Angeles, USA 2008/05/20.

[53] Kawato, M. Towards manipulative neuroscience based on brain-network-interface. Neuroinformatics 2008, Stockholm, Sweden 2008/09/07-09.

[54] Kawato, M. New aspects of BMI. 脳科学研究戦略推進プログラム第１回公開シンポジウム「脳科学の最先端〜BMIと新しいモデル動物〜」, Tokyo, Japan 2009/02/12-13.

[55] Morimoto, J. Implementation of a coupled oscillator model for biped walking. ICORP Collaboration Workshop, Pittsburgh, PA, USA 2007/11/02.

[56] Morimoto, J. Stochastic model-based reinforcement learning for biped locomotion. Humanoids 2007 Workshop: Towards the Realisation of the Computational Brain with Humanoid Robots, Pittsburgh, PA, USA 2007/11/29.

[57] Morimoto, J. Low-dimensional feature extraction for policy improvement. IEEE/RSJ International Conference on Intelligent Robots and Systems Workshop, Nice, France 2008/09/22-26.

[58] Morimoto, J. Biped walking control of a humanoid robot by using monkey's brain activity. International Conference on Robotics and Automation; Workshop, Hyogo, Japan 2009/05/12.

[59] Morimoto, J. Regression on a low-dimensional subspaces to improve policies. Robotics; Science and Systems, Workshop: Regression in Robotics, Seattle, Washington, USA 2009/06/28-07/01.

[60] Morimoto, J. System identification on task relevant dynamics. International Conference on Robotics and Automation; Workshop, Hyogo, Japan 2009/05/17.

[61] Morimoto, J., Nakanishi, J., Endo, G., Cheng, G., Atkeson, C. G., Zeglin, G., & Matsubara, T. Model-based and model-free reinforcement learning methods for biped walking. Robotics: Science and Systems, Workshop on Learning for Locomotion, Cambridge, MA, USA 2005/06/11.

[62] Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., & Kawato, M. Learning and adaptation of biped locomotion with dynamical movement primitives. Robotics: Science and Systems, Workshop on Learning for Locomotion, Cambridge, MA, USA 2005/06/11.

[63] Oztop, E. Modeling mirror neurons. IIAS International Seminar on Language, Evolution, and the Brain, Kyoto, Japan 2007/04/23-27.

[64] Oztop, E., Babic, J., Hale, J. G., Cheng, G., & Kawato, M. Robot behavior synthesis via human motor learning. Humanoids 2007 Workshop: Towards the Realisation of the Computational Brain with Humanoid Robots, Pittsburgh, PA, USA 2007/11/29-12/01.

[65] Oztop, E., Hale, J. G., Babic, J., & Kawato, M. Real-time human control of robots for robot skill synthesis. IEEE-RAS International Conference on Humanoid Robots, Imitation and Coaching in Humanoid Robots Workshop, Daejeon, Korea 2008/12/01-13.

[66] Oztop, E., Hale, J. G., Babic, J., & Kawato, M. Robots as complex tools for humans to control: human visuo-motor learning for robot skill synthesis. IEEE/RSJ International Conference on Intelligent Robots and Systems Workshop on Grasp and Task Learning by Imitation, Nice, France 2008/09/22-26.

[67] Oztop, E., Lin, L., Kawato, M., & Cheng, G. Extensive human training for robot skill synthesis: Validation on a robotic hand. University of Karlsruhe, PACO-PLUS seminar, Karlsruhe, Germany 2007/04/14-17.

[68] Oztop, E., Lin, L., Kawato, M., & Cheng, G. From human motor learning and body schema to robot behavior. Frankfurt Institute for Advanced Studies Seminar, Frankfurt, Germany 2007/04/17.

[69] 玄相昊. ハミルトン系の対称性を利用した走歩行ロボットの制御. 広島大学大学院理学研究科 NLPMセミナー, 広島 2007/07/02.

[70] Oztop, E., Hale, J. G., Babic, J., & Kawato, M. Connecting humans and robots for efficient skill generation, In 2009 IEEE International Conference on Robotics and Automation "Approaches to Sensorimotor Learning on Humanoid Robots" Workshop, Hyogo, Japan (2009).

[71] Oztop, E. Cognitive cybernetics and brain modeling, In 24th International Symposium on Computer and Information Sciences, Northern Cyprus (2009).

[72] 玄相昊. 対称性と受動性に基づく歩容生成と安定化制御. 京都大学理学部数学教室「歩行の数理」研究会, 京都 2007/07/25-26.

[73] 森本淳. 計算論的神経科学とロボティクス. 荒木千里脳外科症例検討研究会 歳末講演会, 大阪 2006/12/19.

[74] 森本淳. 強化学習を用いたロボット制御. 玉川大学JNNS-DEX-SMI公開講座「神経回路網の理論展開と最先端応用」, 東京 2007/03/16-18.

[75] 森本淳. 行動学習のための特徴抽出. JST-ERATO浅田共創知能システムプロジェクト, 大阪大学大学院　吹田キャンパス 2008/09/16.

[76] 森本淳. 行動学習のための特徴抽出. 第11回情報論理的学習理論ワークショップ, 宮城 2008/10/29-31.

[77] 森本淳. 脳情報を用いたロボット制御. 第８回未来医療医工連携倶楽部, 大阪大学大学院　吹田キャンパス 2008/09/16.

[78] 川人光男. コミュニケーションの本質に迫る. 日本体育学会シンポジウム特別講演, 2004/09/25.

[79] 川人光男. ヒューマノイドロボットと脳. 富山県立大学 地域連携公開セミナー 特別講演, 富山 2004/07/09.

[80] 川人光男. ヒューマノイドロボットによる脳研究. 本田技術研究所ワークショップ「計算脳の実現にむけて」特別講演, 2004/09/06.

[81] 川人光男. ブキミの谷をめぐって　真贋のはざま. ルネッサンスジェネレーション'04「前頭葉：決断の一瞬」, 2004/11/20.

[82] 川人光男. ブレインロボットインターフェース. JST異分野研究者交流領域探索研究会「制御生物学の可能性を探る」, 2004/11/29.

[83] 川人光男. ロボットの視覚の計算論. 第60回日本弱視斜視学会特別講演, 2004/06/18-19.

[84] 川人光男. 計算もモデルに基づくイメージング研究. 京都大学　脳のセミナー, 2004/06/29.

[85] 川人光男. 計算論からみた運動制御学習. 東京工業大学特別講義, 2004/12/07.

[86] 川人光男. 計算論からみた運動制御学習. 総合研究大学院大学特別講義, 2004/12/08.

[87] 川人光男. 脳・ロボットと光. スタンレー電気技術展　記念講演, 2004/12/06.

[88] 川人光男. 脳の情報処理の不思議. 日本神経科学学会　市民公開講座, 2004/09/20.

[89] 川人光男. ヒューマノイドロボットと脳. 第53回富山県高等学校教育研究発表大会, 富山 2004/10/07.

[90] 川人光男. ブレイン・ネットワーク・インターフェースと脳科学. NHK技術研究所フロンティア研究講演会, 2005/03/02.

[91] 川人光男. 情報と職業. 京都大学工学部情報学科講義, 2005/06/03.

[92] 川人光男. 情報と職業. SCICE 2005, 2005/06/03.

[93] 川人光男. 相関を超えて因果関係を解き明かす：計算論と復号化によってループを閉じる. 東京大学大学院医学系研究科神経科学入門講義, 2005/04/26.

[94] 川人光男. 脳・人間における情報の処理. 日本賞学術懇談会, 2005/04/19.

[95] 川人光男. 脳とロボットをつなぐインタフェース:ブレイン・ネットワーク・インタフェース. 第13回地域を活かす科学技術政策研修会, 京都 2005/10/19-21.

[96] 川人光男. 脳の計算論とロボティクス. 京都大学大学院情報学研究科 特別講演会, 京都 2005/06/03.

[97] 川人光男. ヒト型ロボットの開発と学習. 富山大学特別講義一般公開, 2006/12/20.

[98] 川人光男. ブレイン・ネットワーク・インターフェースによる操作脳科学. 日本神経回路学会 第16回全国大会, 2006/09/20.

[99] 川人光男. ブレイン・マシン・インターフェースによる操作脳科学. INCF日本ノード設立記念講演会, 2006/02/27.

[100] 川人光男. ブレイン・マシン・インターフェース−脳とネットを繋ぐ技術の現状と未来−. 第4回ATRセミナー, 2006/03/08.

[101] 川人光男. ブレインマシンと脳を活かす研究会. 脊椎損傷者支援イベントWalk Again 2006, 2006/10/09.

[102] 川人光男. 運動制御と小脳内部モデル. 京都大学主催「数学者のための分子生物学入門」勉強会, 2006/01/21.

[103] 川人光男. 脳がいつでもネットにつながる近未来. 第32回WIN定例会「最先端の羽化学が社会生活に与えるインパクト」, 2006/06/07.

[104] 川人光男. 脳でロボットを操作する. サイエンスカフェ 脳の神秘, 2006/12/03.

[105] 川人光男. 脳とネットを結ぶ究極のインターフェース技術の行方−どこまで進む？サイボーグ技術. 関西経済連合会　講演午餐会, 2006/04/03.

[106] 川人光男. 脳を活かす研究動向、脳に学ぶロボット技術. 第6回ヒューマンインターフェースロボット開発研究会, 2006/06/16.

[107] 川人光男. 脳を活かす新しい潮流. フロンティアバイオサイエンスコロキュウム　生命機能研究科第20回研究交流会, 2006/06/14.

[108] 川人光男. 脳を創るから脳を活かすへ. IEEE関西セクション, 2006/12/06.

[109] 川人光男. 脳を創ることによって脳を知る. 生命シンポジウム「生命科学の新しい地平を拓く」, 2006/03/10.

[110] 川人光男. ブレイン・ネットワーク・インターフェース 脳科学はどれほどSFに追いつけるか. 第65回世界SF大会/第46回日本SF大会, 2007/08/30.

[111] 川人光男. ブレイン・ネットワーク・インターフェース：脳とネットを繋ぐ技術の現状と未来. ソニー技術講演, 2007/01/30.

[112] 川人光男. ブレイン・ネットワーク・インターフェースによる未来情報通信. NTTドコモ技術講演会, 2007/09/20.

[113] 川人光男. ブレイン・ネットワーク・インターフェース技術の行方. 日立技術フォーラム2007「脳科学と技術の接点−脳を育む産業へ−, 2007/07/25.

[114] 川人光男. 計算神経科学から操作脳科学へ. 大阪大学基礎工学部生物工学科創立40周年記念講演会, 千里ライフサイエンスセンター 2007/04/28.

[115] 川人光男. 小脳長期抑圧の分子機構と揺らぎの中での安定性. 上原財団「システムズ・バイオロジーの新展開」研究報告会, 2007/05/27.

[116] 川人光男. 脳とネットを結ぶ究極のインターフェース技術の行方−どこまで進む？サイボーグ技術. 第30回日本脳神経CI学会, 2007/02/02.

[117] 川人光男. 脳とロボット. 世界脳週間2006関連イベント「SHH数理講義プログラムIV」脳の不思議を科学する！, 奈良女子大学附属中等教育学校 2007/03/17.

[118] 川人光男. 脳を創ることで脳を知る. 平成19年度「とやま賞」記念講演会, 2007/05/24.

[119] 川人光男. 「脳力」の未来を探る. 同志社大学、朝日新聞共催シンポジウム「脳力」の未来を探る, 2007/07/01.

[120] 川人光男. 複数の脳活動計測方法を用いた情報操作. 第22回日本生体磁気学会学術大会招待講演, 2007/06/21.

[121] 川人光男. ニューラルインターフェースの最前線ーセンサ・計測・応用まで−. 平成20年電気学会全国大会シンポジウム講演, 2008/03/19.

[122] 川人光男. ブレイン・ネットワーク・インターフェース(BMI)技術の最前線. 船井業績賞受賞記念講演会, 2008/09/03.

[123] 川人光男. ブレインインターフェースの最前線. 第５回自然科学研究機構シンポジウム 解き明かされる脳の不思議−脳科学の未来−, 2008/03/20.

[124] 川人光男. 特別講演 脳を繋ぐ研究の最前線. 第45回日本リハビリテーション医学会, 2008/06/04-06.

[125] 川人光男. 特別講演 脳科学が拓く未来社会. 未来工学研究所公開研究発表会, 2008/11/13.

[126] 川人光男. 日本のBMI研究が目指すもの. 生理学研究所 多次元共同脳科学推進センター キックオフシンポジウム, 2008/04/16-18.

[127] 川人光男. 脳・ブレインマシンインターフェース・ロボット. 第30回生理学技術研究会, 2008/02/14.

[128] 川人光男. 脳とロボット. IEEE東京支部総会・講演会, 2008/03/17.

[129] 川人光男. 脳科学と社会の関わり. 第3回「こころの広場」, 2008/12/06.

[130] 川人光男. 脳科学のコンピューティング；BMIからシステムバイオロジー. バイオスーパーコンピューティングシンポジウム2008, 2008/12/25.

[131] 川人光男. 脳科学の社会へのインパクト. 国立情報学研究所オープンハウス基調講演, 2008/06/05.

[132] 川人光男. 脳科学の社会へのインパクト. 東京大学メディアコンテンツ特別講義, 2008/11/14.

International conference

[1] Ariki, Y., Morimoto, J., & Hyon, S. Behavior recognition with ground reaction force estimation and its application to imitation learning, In IEEE/RSJ 2008 International Conference on Intelligent Robots and Systems, pp. 2029-2034, Nice, France (2008).

[2] Azad, P., Ude, A., Asfour, T., Cheng, G., & Dillmann, R. Image-based markerless 3d human motion capture using multiple cues, In International Workshop on Vision Based Human-Robot Interaction, Palermo, Italy (2006).

[3] Azad, P., Ude, A., Dillmann, R., & Cheng, G. A full body human motion capture system using particle filtering and on-fly edge detection, In IEEE-RAS International Conference on Humanoid Robots, pp. 941-959, Santa Monica, CA, USA (2004).

[4] Bentivegna, D. Challenges and issues of selecting and generating actions in robotic imitation systems that operate in dynamic environments, In International Workshop on Robotic Imitation, Sendai, Japan (2004).

[5] Bentivegna, D. C., Atkeson, C. G., & Cheng, G. Learning from observation and practice using primitives, In AAAI Fall Symposium Series/Working Notes: Real-Life Reinforcement Learning, pp. 9-16, Arlington, VA, USA (2004).

[6] Bentivegna, D. C., Atkeson, C. G., & Cheng, G. Combining local and global features to support generalization and learning from practice, In Robotics: Science and Systems, Workshop on Modular Foundations for Control and Perception, MIT, Cambridge, MA, USA (2005).

[7] Bentivegna, D. C., Atkeson, C. G., & Cheng, G. Learning similar tasks from observation and practice, In IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2677-2683, Beijing, China (2006).

[8] Chaminade, T., Franklin, D. W., Oztop, E., & Cheng, G. Motor interference between humans and humanoid robots: Effect of biological and artificial motion, In IEEE International Conference on Development and Learning, pp. 96-101, Osaka, Japan (2005).

[9] Cheng, G. Distributed architecture for humanoid robots perception and control integration, In IEEE-RAS/RSJ International Conference on Humanoid Robots Workshop on Humanoid Technologies, Genova, Italy (2006).

[10] Cheng, G. Humanoid robotics perspectives to neuroscience, In IEEE-RAS/RSJ International Conference on Humanoid Robots Workshop on Towards Cognitive Humanoid Robots, Genova, Italy (2006).

[11] Cheng, G. Humanoid robotics perspectives of neuroscience, In JST-ATR-CMU Joint Workshop, Wakayama, Japan (2007).

[12] Cheng, G., Fitzsimmons, N. A., Morimoto, J., Lebedev, M. A., Kawato, M., & Nicolelis, M. Bipedal locomotion with a humanoid robot controlled by cortical ensemble activity, In Society for Neuuroscience 37th Annual Meeting, San Diego, USA (2007).

[13] Cheng, G., Hyon, S., Morimoto, J., Ude, A., Colvin, G., Scroggin, W., & Jacobsen, S. C. CB: A humanoid research platform for exploring neuroscience, In IEEE-RAS International Conference on Humanoid Robots, pp. 182-187, Genova, Italy (2006).

[14] Cheng, G., Hyon, S., Ude, A., Morimoto, J., Hale, J. G., Nakanishi, J., Hart, J., Bentivegna, D., Hodgins, J., Atkeson, C., Mistry, M., Schaal, S., & Kawato, M. CB: Exploring neuroscience with a humanoid research platform, In 2008 IEEE International Conference on Robotics and Automation, pp. ThA12.4, FrA1.5, FrA1.6, Pasadena, CA, USA (2008).

[15] Endo, G., Morimoto, J., Matsubara, T., Nakanishi, J., & Cheng, G. Learning CPG sensory feedback with policy gradient for biped locomotion for a full-body humanoid, In The Twentieth National Conference on Artificial Intelligence, pp. 1267-1273, Pittsburgh, Pennsylvanis, USA (2005).

[16] Endo, G., Morimoto, J., Nakanishi, J., & Cheng, G. An empirical exploration of a neural oscillator for biped locomotion control, In IEEE International Conference on Robotics and Automation, pp. 3036-3042, New Orleans, LA, USA (2004).

[17] Endo, G., Nakanishi, J., Morimoto, J., & Cheng, G. Experimental studies of a neural oscillator for biped locomotion with QRIO, In IEEE International Conference on Robotics and Automation, pp. 598-604, Barcelona, Spain (2005).

[18] Gumpp, T., Azad, P., Welke, K., Oztop, E., Dillmann, R., & Cheng, G. Unconstrained real-time markerless hand tracking for humanoid interaction, In IEEE-RAS International Conference on Humanoid Robots, pp. 88-93, Genova, Italy (2006).

[19] Gurbuz, S., Shimizu, T., & Cheng, G. Real-time stereo facial feature tracking: Mimicking human mouth movement on a humanoid robot head, In IEEE-RAS International Conference on Humanoid Robots, pp. 363-368, Ibaraki, Japan (2005).

[20] Hale, J. G. Contact handling with static and dynamic friction for dynamically simulated articulated figures, In ACM SIGGRAPH/Eurographics Sysposium on Computer Animation, pp. 27-28, Vienna, Austria (2006).

[21] Hale, J. G. Sub-matrix analysis for contact force resolution in humanoid simulation, In 8th International IFAC Symposium on Robot Control, pp. R-025, Bologna, Italy (2006).

[22] Hale, J. G. Software systems for CB, In JST-ATR-CMU Joint Workshop, Wakayama, Japan (2007).

[23] Hale, J. G., Hohl, B., & Moraud, E. M. Robot simulation, collisions and contacts, In IEEE/RSJ International Conference on Intelligent Robots and Systems Workshop, Nice, France (2008).

[24] Hyon, S. Full-body balance control on CB, In JST-ATR-CMU Joint Workshop, Wakayama, Japan (2007).

[25] Hyon, S. Iterative learning of dynamic full-body motions anchored by joint trajectories, In International Conference on Robotics and Automation, Workshop, Hyogo, Japan (2009).

[26] Hyon, S., & Cheng, G. Gravity compensation and full-body balancing for humanoid robots, In IEEE-RAS International Conference on Humanoid Robots, pp. 214-221, Genova, Italy (2006).

[27] Hyon, S., & Cheng, G. Passivity-based full-body force control for humanoids and application to dynamic balancing and locomotion, In IEEE/RSJ International Conference on Intelligent Robots and Systems 2006, pp. 4915-4922, Beijing, China (2006).

[28] Hyon, S., & Cheng, G. Disturbance rejection for biped humanoids, In IEEE International Conference on Robotics and Automation, pp. 2668-2675, Rome, Italy (2007).

[29] Hyon, S., & Cheng, G. Simultaneous adaptation to rough terriain and unknown external forces for biped humanoids, In IEEE-RAS International Conference on Humanoid Robots, Pittsburg, USA (2007).

[30] Hyon, S. Invariant manifold of symmetric orbits and its application toward globally optimal gait generation for biped locomotion, In 9th International IFAC Symposium on Robot Control, Gifu, Japan (2009).

[31] Hyon, S., Moren, Y., & Cheng, G. Humanoid batting with bipedal balancing, In IEEE-RAS/RSJ International Conference on Humanoid Robots, Daejeon, Korea (2008).

[32] Hyon, S., Morimoto, J., & Cheng, G. Hierarchical motor learning and synthesis with passivity-based controller and phase oscillator, In 2008 IEEE International Conference on Robotics and Automation, pp. 2705-2710, Pasadena, CA, USA (2008).

[33] Hyon, S., Osu, R., & Otaka, Y. Integration of multi-level postural balancing on humanoid robots, In IEEE International Conference on Robotics and Automation, Hyogo, Japan (2009).

[34] Kawato, M. Towards manipulative neuroscience based on brain network interface, In JST-ATR-CMU Workshop, Wakayama, Japan (2007).

[35] Koene, A., Moren, J., Trifa, V., & Cheng, G. Gaze shift reflex in a humanoid active vision system, In International Cognitive Vision Workshop, Bielefeld, Germany (2007).

[36] Matsubara, T., Morimoto, J., Nakanishi, J., Hyon, S., Hale, J. G., & Cheng, G. Learning to acquire whole-body humanoid CoM movements to achieve dynamic tasks with a policy gradient method, In 20th Annual Conference on Neural Information Processing System Workshop: Towards a New Reinforcement Learning?, pp. 2688-2693, Whistler, British Columbia, Canada (2006).

[37] Matsubara, T., Morimoto, J., Nakanishi, J., Hyon, S., Hale, J. G., & Cheng, G. Learning to acquire whole-body humanoid CoM movements to achieve dynamic tasks, In IEEE International Conference on Robotics and Automation, pp. 2688-2693, Rome, Italy (2007).

[38] Matsubara, T., Morimoto, J., Nakanishi, J., Sato, M., & Doya, K. Learning CPG-based biped locomotion with a policy gradient method, In IEEE-RAS International Conference on Humanoid Robots, pp. 208-213, Ibaraki, Japan (2005).

[39] Matsubara, T., Morimoto, J., Nakanishi, J., Sato, M., & Doya, K. Learning sensory feedback to CPG with policy gradient for biped locomotion, In IEEE International Conference on Robotics and Automation, pp. 4175-4180, Barcelona, Spain (2005).

[40] Mistry, M., Nakanishi, J., Cheng, G., & Schaal, S. Inverse kinematics with floating base and constraints for full body humanoid robot control, In IEEE-RAS/RSJ International Conference on Humanoid Robots, Daejeon, Korea (2008).

[41] Mistry, M., Nakanishi, J., Flashner, H., & Schaal, S. Constrained floating base Inverse dynamics without contact forces, In IEEE International Conference on Robotics and Automation, Kobe, Japan (2009).

[42] Mistry, M., Nakanishi, J., & Schaal, S. Task space control with prioritization for balance and locomotion, In IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 331-338, San Diego, CA, USA (2007).

[43] Mistry, M., Theodorou, E., Liaw, G., Yoshioka, T., Schaal, S., & Kawato, M. Adaptation to a sub-optimal desired trajectory, In Society for Neuroscience 38th Annual Meeting, Sattelite Advances in Computational Motor Control VII, Washington D.C., USA (2008).

[44] Mistry, M., Theodorou, E., Liaw, G., Yoshioka, T., Schaal, S., & Kawato, M. An investigation of optimality in reaching movements with an acceleration based force field, In Society for Neuroscience 38th Annual Meeting, Washington D.C., USA (2008).

[45] Miyakoshi, S., & Cheng, G. Examining human walking characteristics with a telescopic compass-like biped walker model, In IEEE International Conference on Systems, Man and Cybernetics, pp. 1538-1543, Hague, Netherlands (2004).

[46] Moraud, E. M., Hale, J. G., & Cheng, G. Constraint-based ground contact handling in humanoid robotics simulation, In 2008 IEEE Internaitonal Conference on Robotics and Automation, Pasadena, CA, USA (2008).

[47] Morimoto, J. Low-dimensional feature extraction for policy improvement, In 2008 IEEE/RSJ International Conference on Intelligent Robotics and Systems Worksshop, Nice, France (2008).

[48] Morimoto, J., Atkeson, C. G., Endo, G., & Cheng, G. Improving humanoid locomotive performance with learnt approximated dynamics via Gaussian processes for regression, In IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4234-4240, San Diego, CA, USA (2007).

[49] Morimoto, J., Endo, G., Nakanishi, J., Hyon, S., Cheng, G., Bentivegna, D. C., & Atkeson, C. G. Modulation of simple sinusoidal patterns by a coupled oscillator model for biped walking, In IEEE International Conference on Robotics and Automation, pp. 1579-1584, Orlando, FL, USA (2006).

[50] Morimoto, J., Hyon, S., Atkeson, C. G., & Cheng, G. Low-dimensional feature extraction for humanoid locomotion using kernel dimension reduction, In 2008 IEEE International Conference on Robotics and Automation, pp. 2711-2716, Pasadena, CA, USA (2008).

[51] Morimoto, J., Nakanishi, J., Endo, G., Cheng, G., Atkeson, C. G., & Zeglin, G. Acquisition of biped walking policy using an approximate poincare map, In IEEE-RAS International Conference on Humanoid Robots, pp. 912-924, Santa Monica, CA, USA (2004).

[52] Morimoto, J., Nakanishi, J., Endo, G., Cheng, G., Atkeson, C. G., & Zeglin, G. Poincare-map-based reinforcement learning for biped walking, In IEEE International Conference on Robotics and Automation, pp. 2392-2397, Barcelona, Spain (2005).

[53] Morimoto, J., Zeglin, G., Atkeson, C. G., & Cheng, G. A simple reinforcement learning algorithm for biped walking, In IEEE International Conference on Robotics and Automation, pp. 3030-3035, New Orleans, LA, USA (2004).

[54] Nakanishi, J. Motor learning and control in humanoid robots, In JST-ATR-CMU Joint Workshop, Wakayama, Japan (2007).

[55] Nakanishi, J., Cory, R., Mistry, M., Peters, J., & Schaal, S. Comparative experiments on task space control with redundancy resolution, In IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1575-1582, Edmonton, Canada (2005).

[56] Nakanishi, J., Farrell, J. A., & Schaal, S. Learning composite adaptive control for a class of nonlinear systems, In IEEE International Conference on Robotics and Automation, pp. 2647-2652, New Orleans, LA, USA (2004).

[57] Nakanishi, J., Mistry, M., Peters, J., & Schaal, S. Towards compliant humanoids - An experimental assessment of suitable task position/orientation controllers, In IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2520-2527, San Diego, CA, USA (2007).

[58] Nakanishi, J., Mistry, M., & Schaal, S. Inverse dynamics control with floating base and constraints, In IEEE International Conference on Robotics and Automation, pp. 1942-1947, Rome, Italy (2007).

[59] Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., & Kawato, M. An empirical exploration of phase resetting for robust biped locomotion with dynamical movement primitives, In IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 919-924, Sendai, Japan (2004).

[60] Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., & Kawato, M. A framework for learning biped locomotion with dynamical movement primitives, In IEEE-RAS International Conference on Humanoid Robots, pp. 925-940, Santa Monica, CA, USA (2004).

[61] Ohtake, S., Yamakita, M., & Hyon, S. Control of underactuated biped running robot via synchronous oscillator, In SICE Annual Conference 2008, pp. 3367-3370, Nice, France (2008).

[62] Oztop, E. Modeling the mirror neurons, In International Workshop on Robotic Imitation, pp. 19-28, Sendai, Japan (2004).

[63] Oztop, E. Extensive human training for robot skill synthesis: validation on a robotic hand, In JST-ATR-CMU Joint Workshop, Wakayama, Japan (2007).

[64] Oztop, E., Babic, J., Hale, J. G., Cheng, G., & Kawato, M. From biologically realistic imitation to robot teaching via human motor learning, In 14th International Conference on Neural Information Processing, pp. WEA-3, 116, Kitakyusyu, Japan (2007).

[65] Oztop, E., Chaminade, T., Cheng, G., & Kawato, M. Imitation bootstrapping: Experiments on a robotic hand, In IEEE-RAS International Conference on Humanoid Robots, pp. 189-195, Ibaraki, Japan (2005).

[66] Oztop, E., Franklin, D. W., & Chaminade, T. Human-humanoid interaction: Is a humanoid robot perceived as human?, In IEEE-RAS International Conference on Humanoid Robots, pp. 830-841, Santa Monica, CA, USA (2004).

[67] Oztop, E., Imamizu, H., Cheng, G., & Kawato, M. A computational model of anterior intraparietal (AIP) neurons, In Computational Neuroscience Meeting, Madison, Wisconsin, USA (2005).

[68] Oztop, E., Lin, L., Kawato, M., & Cheng, G. Dexterous skills transfer by extending human body schema to a robotic hand, In IEEE-RAS International Conference on Humanoid Robots, pp. 82-87, Genova, Italy (2006).

[69] Oztop, E., Lin, L., Kawato, M., & Cheng, G. Extensive human training for robot skill synthesis: Validation on a robotic hand, In IEEE International Conference on Robotics and Automation, pp. 1788-1793, Rome, Italy (2007).

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Patent pending

[1] Hale, J. G. 運動解析方法，運動解析装置，及びコンピュータプログラム, 2008/530955.

[2] Hale, J. G. 運動解析方法、運動解析装置、コンピュータプログラム、及び記録媒体, 特願2008-500562.

[3] Oztop, E. データ分類方法，データ分類装置，及びコンピュータプログラム，及び記録媒体, 特願2007-556932.

[4] Oztop, E. データ分類方法，データ分類装置，及びコンピュータプログラム，及び記録媒体, 12/223530.

[5] Ude, A., Welke, K., Cheng, G., & Hale, J. G. Learning System for Learning Visual Representation of Objects and a Computer Program, 2007-096733.

[6] 遠藤玄, 森本淳, 中西淳, ゴードン・チェン. ロボット装置及びその制御方法, 特願2006-032762.

[7] 遠藤玄, 森本淳, 中西淳, ゴードン・チェン. ロボット装置及びその制御方法, 11/703332.

[8] 遠藤玄, 森本淳, 中西淳, ゴードン・チェン, 松原崇充. ロボット装置及びその制御方法, 特願2006-28875.

[9] 玄相昊. 脚式ロボット及び制御装置, 2008-517955.

[10] 森本淳, 遠藤玄, 中西淳, Cheng, G. Driving method, drive control, apparatus, and robot, 11/799201.

[11] 森本淳, 遠藤玄, 中西淳, ゴードン・チェン. 駆動方法，駆動制御装置及びロボット, 特願2006-128372.

[12] 森本淳, 中西淳, 遠藤玄, ゴードン・チェン, 川人光男. 位相反応曲線学習方法、位相反応曲線学習装置、周期的運動制御方法及び周期的運動制御装置, 2006-251704.

[13] 森本淳, 銅谷賢治. 状態推定方法、状態推定器装置、状態推定システム及びコンピュータプログラム, 特願2005-320988.

Award

[1] 玄相昊. 日本ロボット学会研究奨励賞. (社)日本ロボット学会, 2008/09/10.

[2] 佐藤雅昭, 吉岡琢, 梶原茂樹, 郷田直一, 銅谷賢治, 川人光男. 論文賞. 日本神経回路学会, 2005/09/21.

[3] 川人光男. IEICE FELLOW 社団法人電子情報通信学会, 2004/09/09.

[4] 川人光男. 第58回中日文化賞. 中日新聞社, 2005/05/31.

[5] 川人光男. 情報通信月間推進協議会会長表彰志田林三郎賞. 情報通信月間推進協議会, 2005/06/01.

[6] 川人光男. 朝日賞. 朝日新聞社・財団法人朝日新聞文化財団, 2007/01/29.

[7] 川人光男. APNNA Outstanding Achievement Award. Asia Pacific Neural Network Assembly, 2007/11/15.

[8] 川人光男. Gabor Award. International Neural Networks Society, 2008/06/04.

[9] 川人光男. 第７回船井業績賞. 財団法人船井情報科学振興財団, 2008/09/03.

[10] 大高洋平, 大須理英子, 道免和久, 千野直一, 川人光男. 日本臨床神経生理学会奨励論文賞 日本臨床神経生理学会, 2004/11/18.

[11] 中西淳, S.Schaal, 論文賞. 日本神経回路学会, 2005/09/21.

Media release

[1] 「計算脳」の研究成果発表 ＡＴＲでワークショップ. 産経新聞, 2004/06/29.

[2] 脳を究める つくる６ 学習する人間型ロボット. 日本経済新聞, 2004/08/09.

[3] What we can learn from robots. For Japan's Mitsuo Kawato, robotics explains how the human brain works. MIT's Magazine of Innovation, 2005/01.

[4] 「以心伝心ロボ」へ一歩. 中日新聞, 2006/05/25.

[5] 考えるだけでロボット操作. 日本経済新聞, 2006/05/25.

[6] 考えるだけでロボット動く!? 脳の血流で判断 じゃんけんOK. 岐阜新聞, 2006/05/25.

[7] 失敗から学習する小脳 川人光男さん. 夕刊読売新聞, 2006/07/31.

[8] 念じた通りにジャンケンロボ. 朝日新聞, 2006/05/25.

[9] 脳の血流解析 ロボ遠隔操作. 日刊工業新聞, 2006/05/25.

[10] 鉄腕アトムの時代になった. 産経新聞, 2007/12/12.

[11] The Essence of Japan関西. 関西広域機構　関西報センター（KIPPO) 関西広報DVD, 2008/05.

[12] Ferngesteuert per Gedankenkraft. Berliner Zeitung, 2008/01/18.

[13] James May's Big Ideas. BBC, 2008/10.

[14] Japon: un robot humanoide bipede mu a distance par le cerveau d'un singe. AFP, 2008/01/15.

[15] Monkey Think, Robot Do. Scieutific American (net), 2008/01/15.

[16] Monkey's Thoughts Propel Robot, a Step That May Help Human. THE NEW YORK TIMES, 2008/01/15.

[17] Monkey's Thoughts Propel Robot, a Step That May Help Humans. New York Times (net), 2008/01/16.

[18] NHKスペシャル：ミラクルボディ. NHKスペシャル, 2008/05/04.

[19] サイボーグ出現 SFの世界現実味. 毎日新聞, 2008/01/19.

[20] サルがロボット遠隔操作 日米チーム、世界初. 共同通信, 2008/01/15.

[21] サルが歩くとロボットも＝脳の信号、日米間で伝達−共同研究チーム. 時事通信, 2008/01/15.

[22] サルが歩けばロボットが歩く. 日経サイエンス, 2008/04.

[23] サルが歩けばロボも歩く. 朝日新聞, 2008/01/16.

[24] サルの意思で歩くロボ. 読売新聞, 2008/01/16.

[25] サルの大脳活動の信号でロボットを動かす−JSTとデューク大学が共同研究. Robot Watch (net), 2008/01/24.

[26] サルの脳でロボット動く 科学技術振興機構. asahi.com (net), 2008/01/15.

[27] サルの脳の信号でロボットが歩行 日米チームが成功 パワースーツに応用も. 産経ニュース(net), 2008/01/15.

[28] サルの脳受信 ロボ動く. 朝日新聞　夕刊, 2008/01/16.

[29] サルの脳信号 米から日本へ ロボットで歩行再現. しんぶん赤旗, 2008/01/16.

[30] サルの脳信号伝送 ロボット遠隔操作. フジサンケイ ビジネスアイ, 2008/01/16.

[31] サル大脳皮質の活動データで制御 ヒューマノイドロボ二足歩行に成功. 日刊工業新聞, 2008/01/16.

[32] サル脳が操作するロボット歩行. ロボコンマガジン, 2008/04.

[33] すごいでしょ! 科学のチカラ サルの脳で動くロボット. Cabiネット, 2008/03/15.

[34] ロボット サル脳信号で遠隔操作. 日本経済新聞, 2008/01/16.

[35] ロボット、サル脳信号で遠隔操作−ATRなど日米研究チーム成功. NIKKEI NET Kansai (net), 2008/01/16.

[36] ロボットが”猿まね”、脳の情報受け歩行を再現. YOMIURI ONLINE (net), 2008/01/15.

[37] ロボット猿隔操作. 産經新聞, 2008/01/16.

[38] 世界初、サルの脳信号伝達し、ロボットで再現−ATRなど成功. KIPPO NEWS, 2008/02/06.

[39] 二足歩行ロボット サルの脳情報で遠隔操作. 日経産業新聞, 2008/01/16.

[40] 脳で操る機械 1万キロ先のロボット動く. 日経産業新聞, 2008/10/07.

[41] 脳の信号を受信するロボット. NHKニュース(net), 2008/01/16.

[42] 脳信号 ロボット再現. 毎日新聞, 2008/01/16.

[43] 脳信号でロボット歩行. 京都新聞, 2008/01/16.

[44] 脳信号でロボット歩行 ATR、米大学開発. 京都新聞電子版 (net), 2008/01/16.

[45] 脳信号読み取り遠隔操作 サルが歩けばロボットも歩く. 東京新聞, 2008/01/16.

[46] 脳神経信号をロボットに連動. 奈良新聞, 2008/01/16.

[47] 米国→日本 脳の信号伝達 サル歩けばロボ歩く. 産經新聞, 2008/01/16.

[48] 2足歩行ロボ 動き柔軟. 日経産業新聞, 2009/01/23.

[49] 51関節を持つ二足歩行ロボット「ヒューマノイドロボットCB-i」. 東京IT新聞, 2009/02/10.

[50] ‹ネットはいま›第２部−１６「思い」を伝える. asahi.com (net), 2009/02/24.

[51] ネットはいま第２部 つながる 「思い」を伝える. 朝日新聞, 2009/02/24.

[52] 柔らかい関節でバランス ATRが人型ロボット. 日刊工業新聞, 2009/01/23.

[53] 人間型ロボット「CBi」開発 動き滑らか２足歩行再現. 静岡新聞, 2009/02/08.

[54] 動き滑らか「人間ロボ」脳情報読み歩行再現. 中部経済新聞, 2009/01/31.

[55] 脳の機能計算 複雑な動き再現. 読売新聞, 2009/02/02.

[56] 脳研究で二足歩行再現. 埼玉新聞, 2009/02/04.

[57] 脳神経データで二足歩行も再現. 秋田さきがけ, 2009/02/03.