Neuro-Controller with Simultaneous Perturbation for Robot Arm - Learning of Kinematics and Dynamics without Jacobian
نویسندگان
چکیده
We report two control schemes for a two-link robot arm system using a neuro-controller. We adopted the simultaneous perturbation learning rule for a neuro-controller. Ordinary gradient type of learning rule uses Jacobian of the objective system in a direct control scheme by a neural network. However, the learning rule proposed here requires only two values of an error function. Without Jacobian or related information of the objective robot arm, the neuro-controller can learn an inverse of robot kinematics and dynamics, simultaneously. Some results are shown.
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