遗传算法在Delta机器人刚度优化中的应用  

Application of the Genetic Algorithm in the Optimization of Delta Robot's Stiffness

作　　者：刘冬[1] 张振国[1] 封继军 辛利斌 王顺平[1] 

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《电子科技》2017年第2期33-36,41,共5页Electronic Science and Technology

基　　金：沪江基金资助项目(B1402/D1402)

摘　　要：针对Delta机器人刚度性能指标的优化,提供一种基于其尺度参数切实可行的设计方案。通过逆运动学、雅可比矩阵和刚度公等数学方法,求解该并联机构的刚度和尺度参数之间的函数关系,并以此为目标函数。继而,经过对遗传算法运行机理的分析和对适应度函数、遗传操作的研究,实现了在Matlab环境下的遗传算法求解函数优化问题的仿真。仿真结果表明,该算法可以快速地收敛到全局最优解,适用于在满足Delta机器人设计的其他特性要求的前提下优化机器人机构的刚度。This study focuses on optimizing the stiffness performance indicators of the Delta robot and provides a practical design scheme based on its scale parameter. Firstly, many mathematical methods are quoted, such as the in- verse kinematics, Jacobian matrix, stiffness formula. And then, the relationship between stiffness and scale parameters is derived and set as the objective function. After the operation mechanism of genetic algorithm is analyzed and the fit- ness function and genetic operations are discussed and simulation of the genetic algorithm in optimization is realized in Matlab. The simulation result shows that the genetic algorithm converges to the global optimal solution quickly, and is applicable to optimize the stiffness of robot on the premise of satisfying the design requirements of Delta robots.

关 键 词：遗传算法 Delta机器人 刚度 雅可比矩阵 MATLAB 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置]