Interval Search Genetic Algorithm Based on Trajectory to Solve Inverse Kinematics of Redundant Manipulators and Its Application

Abstract

In this paper, a new method is proposed to solve the inverse kinematics problem of redundant manipulators. This method demonstrates superior performance on continuous motion by combining interval search genetic algorithm based on trajectory which we propose with parametric joint angle method. In this method, population continuity strategy is utilized to improve search speed and reduce evolutionary generation, interval search strategy is introduced to enhance the search ability and overcome the influence of singularity, and reference point strategy is used to avoid sudden changes of joint variables. By introducing those three strategies, this method is especially suitable for redundant manipulators that perform continuous motion. It can not only obtain solutions of inverse kinematics quickly, but also ensure the motion continuity of manipulator and accuracy of the end effector. Moreover, this algorithm can also perform multi-objective tasks by adjusting the fitness function. Finally, this algorithm is applied to an 8 degree of freedom tunnel shotcrete robot. Field experiments and data analysis show that the algorithm can solve the problem quickly in industrial field, and ensure the motion continuity and accuracy.