关键词: 冗余机械臂, 逆运动学, 克隆选择算法, 混合变异

Abstract: To improve the poor convergence quality of Clonal Selection Algorithm (CSA) in solving complex optimization problems,an improved Clonal Selection Algorithm based on Hybrid Mutation (HMCSA) was proposed,which was used to solve the inverse kinematics problem of redundant manipulator.A two-level hybrid cooperative search mode of hybrid differential mutation and clonal selection evolution was adopted to balance the global exploration and local exploitation of the algorithm effectively.Thus,the premature convergence problem of the basic clonal selection algorithm was well overcome.Through the dynamic real-time sharing of successful antibody search experience,the convergence speed of the algorithm was accelerated,and the convergence accuracy of the algorithm was also improved.In addition,compared with the comparison algorithms,the HMCSA had the advantage that fewer parameters needed to be set,which was convenient for the application and promotion of the algorithm.The effectiveness of HMCSA was verified by the classical benchmark function optimization problems.In the optimization of inverse kinematics solution of redundant manipulator,HMCSA also achieved good optimization results,which provided a new idea for solving inverse kinematics problem of robot.

Key words: redundant manipulator, inverse kinematics, clonal selection algorithm, hybrid mutation