Research on Inverse Kinematics Algorithm of 6-DOF Industrial Robot Based on RBF-PID

摘要

Abstract To solve the question of multi value and precision in the process of designing the inverse kinematics controller of 6-DOF Industrial robot, a radial basis function-proportional integral differentiation(RBF-PID) adaptive controller method has been proposed to train the inverse kinematics model of industrial robot. Compared with the traditional RBF neural network, the advantage of RBF-PID adaptive controller was that it had high search efficiency and was not easy to fall into local optimal solution. The simulation results showed that this method could not only overcome the influence of the initial value selection of the traditional RBF neural network learning algorithm on the network performance, but also had a good solution accuracy for the inverse kinematics of the 6-DOF Industrial robot. Compared with the traditional RBF neural network algorithm, the RBF-PID adaptive controller method had improved the performance of overshoot, adjustment time and anti-interference, and solved the problem of solving the multivalued inverse kinematics algorithm.