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Abstract: The redundant humanoid manipulator has characteristics of multiple degrees of freedom and complex joint structure, and it is not easy to obtain its inverse kinematics solution. The inverse kinematics problem of a humanoid manipulator can be formulated as an equivalent minimization problem, and thus it can be solved using some numerical optimization methods. biogeography-based optimization (BBO) is a new biogeography inspired optimization algorithm, and it can be adopted to solve the inverse kinematics problem of a humanoid manipulator. The standard BBO algorithm that uses traditional migration and mutation operators suffers from slow convergence and prematurity. A hybrid biogeography-based optimization (HBBO) algorithm, which is based on BBO and differential evolution (DE), is presented. In this hybrid algorithm, new habitats in the ecosystem are produced through a hybrid migration operator, that is, the BBO migration strategy and DE/best/1/bin differential strategy, to alleviate slow convergence at the later evolution stage of the algorithm. In addition, a Gaussian mutation operator is adopted to enhance the exploration ability and improve the diversity of the population. Based on these, an 8-DOF (degree of freedom) redundant humanoid manipulator is employed as an example. The end-effector error (position and orientation) and the ‘away limitation level’ value of the 8-DOF humanoid manipulator constitute the fitness function of HBBO. The proposed HBBO algorithm has been used to solve the inverse kinematics problem of the 8-DOF redundant humanoid manipulator. Numerical simulation results demonstrate the effectiveness of this method.

This paper proposes a hybrid optimization algorithm of Biogeography-based Optimization (HBBO) based on the improvement of BBO algorithm and differential evolution (DE) to deal with the inverse kinematics problem of humanoid manipulator. The algorithm allows for generation of new habitats in ecosystem through a hybrid migration operator, which can speed up the convergence of the algorithm. Gaussian mutation operator is also used to enhance the exploration ability and improve the diversity of the population. Numerical simulation has been performed to demonstrate the effectiveness of the proposed method to determine the solution for the inverse kinematics of an 8-DOF redundant humanoid manipulator, which also shows its potentials to be applied to practice in real time, and other redundant manipulators as well. The paper presents the novelty for solution of the inverse kinematics.

基于混合生物地理学优化的8自由度冗余臂逆运动学求解

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