Abstract
The paper deals with structures of multi-sensory feedback in advanced robot control systems. The sensor programming technique, based on an automatic generation of the “constraint frames” and a projection of teacher-incuced rudimentary path commands into these constraint frames is outlined. Robots with arbitrarily programmable stiffness are one outcome of this technique. Concepts for learning, recall and matching of nominal multisensory patterns are outlined. Supervised learning is discussed by hand of a grinding problem. One of the experiments shown is a two-arm cooperative robot system.
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