Solving Approach of Inverse Kinematics for Manipulators Based on Improved Adaptive Niche Genetic Algorithm

Abstract

Solving the inverse kinematics for a manipulator is of great importance to the manipulator's pose control and trajectory planning. Aiming at the poor generality and difficulty of finding an optimal solution from the multiple inverse kinematics solutions, a novel solution approach based on the modified adaptive niche genetic algorithm is proposed in this study. The principle of 'most suppleness' is integrated into the fitness function such that the only optimal solution can be found; The clustering is introduced into the approach for enhancing the generality and the genetic algorithm is improved for increasing the convergence speed and accuracy. Simulation results based on a six degree of freedom manipulator show that the proposed approach is effective and high precision, and can find the optimal solution.

Keywords

• inverse kinematics (ik)
• manipulator
• adaptive niche
• genetic algorithm
• optimal solution