基于Kriging算法与PSO算法的桁架机器人横梁模块智能优化设计方法

桁架机器人搬运能力强、操作方便、定位精度高，在制造业中具有极其重要的作用。 针对桁架机器人自重大而导致的运行稳定性较差和材料冗余等问题进行结构优化设计研究。目前桁架机器人的结构优化设计研究有限元仿真有限元仿真调用次数多，时间损耗大，优化效率低。针对此问题，在分析了桁架机器人横梁部件尺寸、负载与应力、形变之间的关系后，提出了一种基于Kriging模型与粒子群算法的结构优化设计方法，可以有效减少有限元仿真的调用次数，节约时间，提高优化设计效率。

Truss Robot Based on Kriging Algorithm PSO AlgorithmIntelligent optimization design method of beam module

The truss robot has strong handling ability, convenient operation and high positioning accuracy, and plays an extremely important role in the manufacturing industry. Aiming at the problems of poor operation stability and material redundancy caused by the weight of the truss robot, structural optimization design research is carried out. At present, the finite element simulation of truss robot structure optimization design research has many times of finite element simulation calls, large time loss and low optimization efficiency. In order to solve this problem, after analyzing the relationship between the size, load, stress and deformation of the beam components of the truss robot, a structural optimization design method based on the Kriging model and particle swarm algorithm is proposed, which can effectively reduce the number of calls of finite element simulation. , save time and improve the efficiency of optimized design.