Abstract
In this paper, we propose a learning algorithm for coordinating a robot system where the movement of an arm is controlled through a stereo camera system. Instead of calibrating the usually complex non-linear transformation between the arm and cameras, the algorithm decomposes the whole transformation automatically into local linear transformations and then makes the linearization map recorded by the arm controller. The linearization is carried out by a learning process based on a Kohonen-style self-organization network. To deal with unstructured environments in which some obstacles exist, some virtual forces are introduced for dealing with the high degree of complexity underlying in the transformation.
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Zha, H., Onitsuka, T. & Nagata, T. A self-organization learning algorithm for visuo-motor coordination in unstructured environments. Artificial Life and Robotics 1, 131–136 (1997). https://doi.org/10.1007/BF02471127
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DOI: https://doi.org/10.1007/BF02471127