Research on Motion Control Strategy of Flexible Manipulator Based on Swarm Intelligence Optimization

Abstract

The requirement for motion control of robotic arms in industrial settings is a dynamic field. This study examines the principles and derivation of the kinematics of the robotic arm based on the D-H parameter model. Additionally, the introduction of the seventh joint is proposed as a faster solution for solving the inverse kinematics of the robotic arm. Swarm intelligence optimization for path planning is currently advancing, and our proposed improved algorithm, the Golden Eagle search algorithm, enhances the traditional Golden Eagle search algorithm Jining by integrating a stochastic gradient descent strategy and Cauchy mutation strategy. We compare our IGEO algorithm with various other algorithms, and the findings demonstrate that the robotic arm can adeptly circumnavigate obstacles while walking seamlessly through environments with multiple obstacles. The IGEO algorithm is adept at navigating paths obstructed by multiple obstacles. It improves the accuracy by 15.38% as compared to the conventional algorithm and also improves it a lot as compared to other optimisation algorithms by up to 29.88%. It provides a solution to the path planning problem of robotic arms with excellent robustness and accuracy in finding the shortest collision-free path.