山口 明彦, 工学博士

研究分野

ロボットラーニング; 行動学習; 強化学習; 機械学習; ディープラーニング; 人工知能; ロボティクス; ヒューマノイドロボット; 柔軟物体の操作; 液体の操作; フィンガービジョン

最新情報はこちらから：

• 論文: ResearchGate
• 動画: YouTube Channel
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代表的な文献

• Akihiko Yamaguchi, and Christopher G. Atkeson:
  Tactile Behaviors with the Vision-Based Tactile Sensor FingerVision,
  International Journal of Humanoid Robotics, Vol.16, No.03, 2019. [final-draft] [World Scientific]
• Akihiko Yamaguchi, and Christopher G. Atkeson:
  Recent progress in tactile sensing and sensors for robotic manipulation: can we turn tactile sensing into vision?,
  Advanced Robotics, Vol.33, No.14, pp.661-673, 2019.
  DOI:10.1080/01691864.2019.1632222 [final-draft] [Taylor & Francis]
• Akihiko Yamaguchi and Christopher G. Atkeson:
  Implementing Tactile Behaviors Using FingerVision,
  in Proceedings of the 17th IEEE-RAS International Conference on Humanoid Robots (Humanoids2017), Birmingham, UK, 2017. [final-draft] [Video]
• Akihiko Yamaguchi and Christopher G. Atkeson:
  Stereo Vision of Liquid and Particle Flow for Robot Pouring,
  in Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots (Humanoids2016), Cancun, Mexico, 2016. [final-draft] [Video]
• Akihiko Yamaguchi and Christopher G. Atkeson:
  Combining Finger Vision and Optical Tactile Sensing: Reducing and Handling Errors While Cutting Vegetables,
  in Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots (Humanoids2016), Cancun, Mexico, 2016. [final-draft] [Video]
• Akihiko Yamaguchi and Christopher G. Atkeson:
  Differential Dynamic Programming for Graph-Structured Dynamical Systems: Generalization of Pouring Behavior with Different Skills,
  in Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots (Humanoids2016), Cancun, Mexico, 2016. [final-draft] [Video]
• Akihiko Yamaguchi and Christopher G. Atkeson:
  Neural Networks and Differential Dynamic Programming for Reinforcement Learning Problems,
  in Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA2016), pp. 5434-5441, Stockholm, Sweden, May, 2016. [final-draft] [Video]
• Akihiko Yamaguchi and Christopher G. Atkeson:
  Differential Dynamic Programming with Temporally Decomposed Dynamics,
  in Proceedings of the 15th IEEE-RAS International Conference on Humanoid Robots (Humanoids2015), pp. 696-703, Seoul, 2015. [final-draft] [Video]
• Akihiko Yamaguchi, Christopher G. Atkeson, and Tsukasa Ogasawara:
  Pouring Skills with Planning and Learning Modeled from Human Demonstrations,
  International Journal of Humanoid Robotics, Vol.12, No.3, pp.1550030, July, 2015. [final-draft+col-figs] [World Scientific] [Video]
• Akihiko Yamaguchi, Jun Takamatsu, and Tsukasa Ogasawara:
  DCOB: Action space for reinforcement learning of high DoF robots,
  Autonomous Robots, Vol.34, No.4, pp.327-346, May, 2013. [PDF] [Springer] [Video]
• Akihiko Yamaguchi, Shiori Sato, Kentaro Takemura, Jun Takamatsu, and Tsukasa Ogasawara:
  Style Translation Filter to Change Attribute of Motion,
  in Proceedings of the 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids2012), pp.660-665, Osaka, Japan, December 1, 2012. [final-draft]
• Gustavo Alfonso Garcia Ricardez, Akihiko Yamaguchi, Jun Takamatsu, and Tsukasa Ogasawara:
  Asymmetric Velocity Moderation: a Reactive Strategy for Human Safety,
  in Proceedings of the 10th IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR2012), 56 (S7A-2), Texas, US, November 7, 2012.
• Emarc Magtanong, Akihiko Yamaguchi, Kentaro Takemura, Jun Takamatsu, and Tsukasa Ogasawara:
  Inverse Kinematics Solver for Android Faces with Elastic Skin,
  Latest Advances in Robot Kinematics, pp.181-188, Innsbruck, Austria, June 26, 2012. [final-draft]
• Akihiko Yamaguchi, Jun Takamatsu, and Tsukasa Ogasawara:
  Learning Strategy Fusion to Acquire Dynamic Motion,
  in Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids2011), pp.247-254, Bled, Slovenia, 2011. [final-draft]
• Akihiko Yamaguchi, Jun Takamatsu, and Tsukasa Ogasawara:
  Fusing Learning Strategies to Learn Various Tasks with Single Configuration,
  IEICE Technical Report, Vol.110, No.461, NC2010-154, pp.159-164, March 2011. [final-draft]
• Akihiko Yamaguchi, and Tsukasa Ogasawara:
  SkyAI: Highly Modularized Reinforcement Learning Library ---Concepts, Requirements, and Implementation---,
  in Proceedings of the 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids2010), pp.118-123, Nashville, TN, US, 2010. [final-draft]
• Akihiko Yamaguchi, Sang-Ho Hyon, and Tsukasa Ogasawara:
  Reinforcement Learning for Balancer Embedded Humanoid Locomotion,
  in Proceedings of the 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids2010), pp.308-313, Nashville, TN, US, 2010. [final-draft]