Inverse Kinematics Solution for Manipulators Based on the Artificial Evolved Hummingbird Algorithm

Aiming at the current stage of inverse kinematics solving methods for multi-degree-of-freedom manipulators, most of which have the problems of low solving accuracy and poor generalization, an artificial evolved hummingbird algorithm (AEHA) was proposed for inverse kinematics solving of manipulators. Taking the six-degree-of-freedom manipulator as the research object, a nonlinear equation system of its inverse kinematics was established; taking the position error of the end of the manipulator as the optimization objective, the fitness function was constructed by combining with the energy loss, so as to transform the inverse kinematics problem into the optimization problem of the objective function, and the proposed algorithm was used to solve the problem. The artificial hummingbird evolutionary algorithm improved the ability of the algorithm to get rid of the local optimum by introducing the Sobol sequence and the Levy flight strategy; the differential evolution strategy was introduced to realize the cross-evolution between individuals to avoid the premature convergence. Then, the proposed algorithm was verified that it had the good convergence accuracy by benchmark function test experiments. Finally, the inverse kinematics solving simulation was carried out on a six-axis manipulator. The results show that the artificial evolution hummingbird algorithm is better than the comparison algorithm in terms of solving accuracy and stability, and the solving accuracy can reach 10^-9 mm, which can be applied to the inverse kinematics solving of multi-degree-of-freedom manipulators.