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基于近似模型的重载仿生腿多目标优化
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Multi-objective Optimization of Heavy-duty Bionic Leg Structure Based on Approximate Model
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    摘要:

    针对大型六足机器人在运动过程中腿部刚度不足和振动的问题,提出一种基于近似模型的多目标综合优化方法. 建立有限元模型,分析各类复杂工况下腿部结构强度、刚度 和模态频率等性能,确定仿生腿的优化空间. 对仿生腿静态及动态性能建立参数化模型,定义相应的设计变量,采用优化拉丁超立方方法分别对仿生腿基节、大腿和小腿模块进行试验设计,获取初始样本点,拟合各模块响应面模型、克里格模型和径向基函数神经网络模型,通过误差分析选定精度最高的近似模型,并联合第二代非支配排序遗传算法,以静态刚度、质量和首阶固有频率为目标,约束最大应力,对仿生腿进行优化设计,对优化后的结果进行分析验证. 结果表明,重载仿生腿经所述方法优化后,在满足结构强度的前提下,平地工况最大变形下降9.73%,斜坡工况最大变形下降9.46%,首阶固有频率提升3.45%,仿生腿总体质量下降8.63%.

    Abstract:

    Aiming at the problems of insufficient leg stiffness and vibration of large hexapod robots during motion, a multi-objective comprehensive optimization method based on an approximate model is proposed. First, to determine the optimal space for the bionic leg, a finite element model is established to analyze the strength, stiffness, and modal frequency of the leg structure under various complex working conditions. A parametric model is established for the static and dynamic performance of the bionic leg, and the corresponding design variables are defined. To obtain the initial sample points, the Optimal Latin Hypercube Method was used to conduct an experimental design of the bionic leg hip linkage, thigh, and calf module. The response surface model, kriging model and radial basis function neural network model are fitted, and the approximate model with the highest accuracy is selected through error analysis. And combined with the Non-dominated Sorting Genetic Algorithm Ⅱ, the static stiffness, mass, and first-order natural frequency are targeted.Constraining the maximum stress, the bionic leg is optimally designed, and the optimized results are analyzed and verified. The results show that after the heavy-duty bionic leg is optimized by the method, under the premise of satisfying the structural strength, the maximum deformation of the flat ground condition is reduced by 9.73%, the maximum deformation of the slope condition is reduced by 9.46%, the first-order natural frequency is increased by 3.45%, and the overall quality fell by 8.63%.

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陈伟, 谭旭瑞, 杨阔 ?, 刘昕晖.基于近似模型的重载仿生腿多目标优化[J].湖南大学学报:自然科学版,2023,(6):80~89

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  • 在线发布日期: 2023-07-05
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