A real-time inverse kinematics solution based on joint perturbation for redundant manipulators

Abstract

Aiming at the problem that the calculation of the inverse kinematics solution of redundant manipulators is very time-consuming, this paper presents a real-time method based on joint perturbation and joint motion priority. The method first seeks the pose nearest to the target pose in the manipulator's pose set through fine-tuning all the joints with different angle deviations at the same time and then regards this pose as the starting one to perform iterative calculations until the error between the current pose and the target pose is less than the predetermined error, thus obtaining the inverse kinematics solution corresponding to the target pose. This method can avoid the pseudo-inverse calculations of the Jacobian matrix and significantly reduce the solving complexity. Two types of manipulators are taken as examples to validate the proposed method. Under the premise that the manipulator motion trajectory is satisfied, the Jacobian pseudo-inverse method and the proposed method are both adopted to solve the inverse kinematics. Simulations and comparisons show that the proposed method has better real-time performance, and the joint motions can be flexibly controlled by setting different joint motion priorities. This method can make the work cycle faster and improve the production efficiency of redundant manipulators in real applications.