并联机器人位姿正解优化算法及其仿真  

OPTIMIZATION ALGORITHM OF FORWARD POSE SOLUTION TO PARALLEL ROBOT AND ITS SIMULATION

作　　者：李穆远 全惠敏[1] 吴桂清[1] 

机构地区：[1]湖南大学电气与信息工程学院,湖南长沙410082

出　　处：《计算机应用与软件》2017年第12期260-265,共6页Computer Applications and Software

基　　金：国家科技支撑计划项目(2014BAK08B01)

摘　　要：选取3-6结构并联机器人为研究模型,根据构型间的约束关系,建立机构的位姿正解的求解模型,并采用改进粒子群算法进行求解,将复杂的位姿正解问题转化为多元非线性方程的寻优过程。为提高求解精度,利用混沌序列的不可预测性与无序性以及在一定范围内不重复遍历所有状态的特性,提出一种基于混沌序列调整惯性权重的改进粒子群算法,将其用于求解位姿正解的计算。计算实例表明,该算法能求解出全部的位姿正解,且相较于标准粒子群算法能达到更高的收敛精度。最后采用Solid Works和Adams进行联合仿真,验证了这种优化算法的可行性。In this paper, 3 -6 structure parallel manipulators are chosen as the research model. According to the constraint relation between configurations, an unconstrained optimization model is established for solving the forward position problem of the parallel platform. The complicated kinematics problem is transformed into a multiple nonlinear equations optimization process. In order to improve the convergence precision of the algorithm, an improved particle swarm optimization based on the chaotic sequence was proposed. Ergodic, stochastic and regular properties are the characteristics of chaos, which means it can track any state in a certain scope without repetition according to its regularity, using chaotic sequence to adjust the inertia weight was proposed in this paper, And used this improved particle swarm optimization to solve the forward position problem. Results of a numerical for the forward position analysis of the parallel platform show that, the improved particle swarm algorithm could solve all the position positive solutions, and compared to the standard particle swarm optimization algorithm can achieve higher convergence accuracy. At last, SolidWorks and Adams were used for co-simulation test. And the feasibility of the algorithm was verified.

关 键 词：位姿正解 粒子群算法 混沌序列 惯性权重 ADAMS仿真 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]