Delta并联机器人机构多目标优化设计

Multi-objective Optimization Design of Delta Parallel Robot Mechanism

针对Delta并联机构设计中存在的问题,研究Delta并联机构动力学模型、运动学模型等,并探讨一种求解Delta并联机器人尺度综合问题的设计方法。通过对Delta机器人的主要尺寸参数与6项性能指标进行试验设计,将性能指标合并为3个优化目标函数。在iSIGHT软件平台上运用非支配排序遗传算法(NSGA-Ⅱ),在特定轨迹下对3-DOF Delta并联机构进行尺度综合;对比两种优化策略下目标函数的Pareto图。结果表明:减少目标函数后的优化策略收敛性好、计算费用低,且有更多可行性解。

Aiming at the problems in the structural design of the Delta parallel mechanism,the dynamic model and kinematic model of the Delta parallel mechanism were studied,and a design method to solve the comprehensive problem of the Delta parallel robot scale was discussed.Through the design of experiment on the main dimensional parameters and 6 performance indicators of the Delta robot,the performance indicators were combined into 3 optimization objective functions.By using non-dominated sorting genetic algorithmⅡon the iSIGHT software platform,the 3-DOF Delta parallel mechanism was comprehensively scaled under a specific trajectory;the Pareto charts of the objective functions under the two optimization strategies were compared.The results show that the optimization strategy after reducing the objective function has good convergence,low computational cost,and more feasible solutions.