基于改进型遗传算法的虚拟人上肢运动链逆运动学求解方法  

Solution method for inverse kinematics of virtual human's upper limb kinematic chain based on improved genetic algorithm

作　　者：邓刚锋[1] 黄先祥[1] 高钦和[1] 张志利[1] 李敏[1] 

机构地区：[1]兵器发射理论与控制技术国家重点实验室(第二炮兵工程大学),西安710025

出　　处：《计算机应用》2014年第1期129-134,174,共7页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61102170);国防预研基金资助项目(9140A27040112JB47081)

摘　　要：由于人体上肢运动链的高自由度,用传统的几何法、解析法、迭代法等求其逆解较为困难。遗传算法具有很好的寻优特性,但标准遗传算法在求解时容易陷入早熟收敛和后期搜索迟钝。为此,提出了一种改进型遗传算法(IGA)求解的方法。先构建人体上肢运动链的各关节单元,并用D-H方法建立其数学模型;然后仿人类种群现象实现遗传算法的种群多样化和种群初始化,设计具有自适应性能的交叉概率和变异概率算子,从而完成了对标准遗传算法的改进。通过对比仿真计算结果可得,改进后的遗传算法能以更大概率避免陷入早熟收敛和后期搜索迟钝,并以较少的遗传代数寻得高精度逆解。An Improved Genetic Algorithm （IGA） was proposed for the inverse kinematics problem solution of upper limb kinematic chain which had high degree of freedom and was too complex to be solved by using geometric, algebraic, and iterative methods. First, the joint-units of upper limb kinematic chain and its mathematical modeling were constructed by using Denavit-Hartenberg （D-H） method, then population diversity and initialization were completed based on simulating human being population, and the adaptive operators for crossover and mutation were designed. The simulation results show that the IGA can search the high precise solutions and avoid prematurity convergence or inefficient searching in later stage with larger probability than standard genetic algorithm.

关 键 词：上肢运动链 逆向运动学 D—H方法 遗传算法 种群初始化 

分 类 号：TP391.98[自动化与计算机技术—计算机应用技术]