Abstract
This article presents an intelligent control system for a redundant manipulator to avoid physical limits such as joint angle limits and joint velocity limits. In this method, a back-propagation neural network (NN) is introduced for the kinematic inversion of the manipulator. Since this inverse kinematics has an infinite number of joint angle vectors, a fuzzy-neuro system is constructed to provide an approximate value for that vector. This vector is fed into the NN as a hint input vector in order to guide the output of the NN within the self-motion. Simulations and a comparative study are made based on a four-link redundant manipulator to prove the efficacy of the proposed control system.
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Assal, S., Watanabe, K. & Izumi, K. Intelligent control for avoiding the joint limits of redundant planar manipulators. Artif Life Robotics 10, 141–148 (2006). https://doi.org/10.1007/s10015-005-0370-8
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DOI: https://doi.org/10.1007/s10015-005-0370-8