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Dynamics and Robust Control of Robot-Environment Interaction

, , , and . New Frontiers in Robotics World Scientific, (2009)

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A neural network-based classification of environment dynamics models for compliant control of manipulation robots., and . IEEE Trans. Syst. Man Cybern. Part B, 28 (1): 58-69 (1998)New Trends in Robotic Reinforcement Learning: Single and Multi-robot Case.. Towards Intelligent Engineering and Information Technology, volume 243 of Studies in Computational Intelligence, Springer, (2009)Learning control algorithms for robot contact task using feedforward neural networks., and . IROS (3), page 522-527. IEEE Computer Society, (1995)Policy gradient fuzzy reinforcement learning control of humanoid walking., and . ICONS, page 98-103. International Federation of Automatic Control, (2009)Survey of Intelligent Control Techniques for Humanoid Robots., and . Journal of Intelligent and Robotic Systems, 37 (2): 117-141 (2003)The Application of Connectionist Structures to Learning Impedance Control in Robotic Contact Tasks., and . Appl. Intell., 7 (4): 315-326 (1997)An Integrated Approach for Efficient Mobile Robot Trajectory Tracking and Obstacle Avoidance., , and . ICINCO (2), page 211-216. SciTePress, (2012)Highly efficient robot dynamics learning by decomposed connectionist feedforward control structure., and . IEEE Trans. Syst. Man Cybern., 25 (1): 145-158 (1995)Using Neural Network Model for Learning Control of Manipulation Robots.. IAS, page 424-433. IOS Press, (1989)Hybrid Dynamic Control Algorithm for Humanoid Robots Based on Reinforcement Learning., , and . J. Intell. Robotic Syst., 51 (1): 3-30 (2008)