Hybrid taguchi DNA swarm intelligence for optimal inverse kinematics redundancy resolution of six-DOF humanoid robot arms

Abstract

This paper presents a hybrid Taguchi deoxyribonucleic acid (DNA) swarm intelligence for solving the inverse kinematics redundancy problem of six degree-of-freedom (DOF) humanoid robot arms. The inverse kinematics problem of the multi-DOF humanoid robot armis redundant and has no general closed-formsolutions or analytical solutions.The optimal joint configurations are obtained by minimizing the predefined performance index inDNAalgorithmfor real-world humanoid robotics application.The Taguchi method is employed to determine the DNA parameters to search for the joint solutions of the six-DOF robot arms more efficiently. This approach circumvents the disadvantage of time-consuming tuning procedure in conventional DNA computing. Simulation results are conducted to illustrate the effectiveness and merit of the proposed methods. This Taguchi-based DNA (TDNA) solver outperforms the conventional solvers, such as geometric solver, Jacobian-based solver, genetic algorithm (GA) solver and ant, colony optimization (ACO) solver.