Learning Inverse Kinematics: Reduced Sampling Through Decomposition Into Virtual Robots

We propose a technique to speedup the learning of the inverse kinematics of a robot manipulator by decomposing it into two or more virtual robot arms. Unlike previous decomposition approaches, this one does not place any requirement on the robot architecture, and thus, it is completely general. Parametrized self-organizing maps are particularly adequate for this type of learning, and permit comparing results directly obtained and through the decomposition. Experimentation shows that time reductions of up to two orders of magnitude are easily attained.

[1]  Carme Torras,et al.  Speeding up the learning of robot kinematics through function decomposition , 2005, IEEE Transactions on Neural Networks.

[2]  C. S. G. Lee,et al.  Robotics: Control, Sensing, Vision, and Intelligence , 1987 .

[3]  Carme Torras,et al.  Self-calibration of a space robot , 1997, IEEE Trans. Neural Networks.

[4]  Carme Torras.  Robot control , 1998 .

[5]  Carme Torras,et al.  Using PSOMs to Learn Inverse Kinematics Through Virtual Decomposition of the Robot , 2005, IWANN.

[6]  Klaus Schulten,et al.  Implementation of self-organizing neural networks for visuo-motor control of an industrial robot , 1993, IEEE Trans. Neural Networks.

[7]  Stefan Schaal,et al.  Learning inverse kinematics , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[8]  Helge J. Ritter,et al.  Neural computation and self-organizing maps - an introduction , 1992, Computation and neural systems series.

[9]  Stefan Schaal,et al.  Statistical Learning for Humanoid Robots , 2002, Auton. Robots.

[10]  Carme Torras,et al.  Learning Inverse Kinematics via Cross-Point Function Decomposition , 2002, ICANN.

[11]  Helge J. Ritter,et al.  Rapid learning with parametrized self-organizing maps , 1996, Neurocomputing.

[12]  Helge J. Ritter,et al.  Three-dimensional neural net for learning visuomotor coordination of a robot arm , 1990, IEEE Trans. Neural Networks.