现代制造工程 ›› 2025, Vol. 543 ›› Issue (12): 121-129.doi: 10.16731/j.cnki.1671-3133.2025.12.015

• 设备设计/诊断维修/再制造 • 上一篇    下一篇

复合机器人车架结构优化设计

陈亚1, 李旭静1, 张磊2, 王殿君1, 刘丁赫1, 王鹏3, 刘淑晶1   

  1. 1 北京石油化工学院机械工程学院,北京 102617;
    2 北京电子科技职业学院,北京 100176;
    3 北京石油化工学院信息工程学院,北京 102617
  • 收稿日期:2024-11-25 出版日期:2025-12-18 发布日期:2026-01-06
  • 作者简介:陈亚,博士,副教授,主要研究方向为机器人系统建模与分析。李旭静,硕士研究生,主要研究方向为机器人技术。张磊,硕士,讲师,主要研究方向为金属材料焊接。王殿君,博士,教授,主要研究方向为机器人技术及应用。刘丁赫,硕士研究生,主要研究方向为移动机器人设计。王鹏,博士,讲师,主要研究方向为复合机器人协同一体化控制。刘淑晶,硕士,高级实验师,主要研究方向为机器人技术。E-mail:chenya@bipt.edu.cn
  • 基金资助:
    *工业和信息化部2022年复合机器人项目(TC220H05D);北京市教育委员会科研计划项目(KM202410017007)

Structural optimization design of composite robot frame

CHEN Ya1, LI Xujing1, ZHANG Lei2, WANG Dianjun1, LIU Dinghe1, WANG Peng3, LIU Shujing1   

  1. 1 College of Mechanical Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617,China;
    2 Beijing Electronic Technology Vocational College,Beijing 100176,China;
    3 College of Information Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617,China
  • Received:2024-11-25 Online:2025-12-18 Published:2026-01-06

摘要: 为了提高复合机器人车架的结构性能,采用多目标优化方法设计了一种轻质量、高负载的双层矩形车架结构,该结构能够使复合机器人在行驶过程中受力均衡,降低移动干涉,从而提高行驶过程的稳定性。基于静力学分析,构建以车架长度、高度以及矩形管厚度为优化变量,以车架质量、变形量为优化目标的多目标优化模型,基于最优空间填充和拉丁超立方取样复合实验设计方法,采用改进的多目标非支配排序遗传算法进行求解。结果表明,优化后的车架质量和最大变形量大幅减小,其中车架质量减小了29.7 %,最大变形量减小了21.5 %。同时,优化后结构的强度和刚度均满足使用要求,这对于复合机器人车架的轻量化设计具有一定的参考价值。

关键词: 复合机器人, 双层矩形车架, 多目标非支配排序遗传算法, 优化设计

Abstract: To improve the structural performance of the composite robot frame,a multi-objective optimization method was used to design a light-weight,high-load double-layer rectangular frame structure. The structure enabled the composite robot to maintain balanced forces and reduce movement interference,and enhance the stability of the driving process.Based on the static analysis,a multi-objective optimization model was constructed with the frame length,height and the thickness of the rectangular tubes as the optimization variables,and the mass and deformation of the frame as the optimization objectives.Based on the Optimal Space-Filling (OSF) and the Latin Hypercube Sampling (LHS) composite experimental design method,the optimization model was solved by improved multi-objective Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ). The results show that the mass and maximum deformation of the optimized frame are significantly reduced,in which the frame mass is reduced by 29.7 % and the maximum deformation is reduced by 21.5 %. Meanwhile,the strength and stiffness of the optimized structure meet the usage requirements,providing certain reference value for the lightweight design of composite robot frame.

Key words: composite robots, double-layer rectangular frame, Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ), optimization design

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