SoRoTop:基于设计的气动驱动软机器人拓扑优化MATLAB代码指南

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Prabhat Kumar
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引用次数: 0

摘要

各种应用对气动驱动软机器人的需求不断上升。然而,由于缺乏系统的方法,它们往往是手工设计的。此外,气动驱动的设计依赖特性带来了独特的挑战。本文提供了一个紧凑的MATLAB代码SoRoTop及其各种扩展,用于利用拓扑优化设计气动驱动软机器人。该代码使用移动渐近线的方法作为优化器,并基于Kumar等人最初提出的方法(Struct multidisciplp Optim 61(4): 1637-1655, 2020)。采用达西定律对气动载荷进行建模,并对排水项进行了概念化。用传统的有限元方法从合成压力场确定一致节点荷载。采用稳健公式,即采用侵蚀式和蓝图式设计描述。利用侵蚀和蓝图设计的输出位移,建立了最小-最大优化问题。在蓝图设计中施加了体积约束,而侵蚀设计用于应用概念化的应变能约束。后一种约束有助于获得优化设计,可以承受施加的负载而不影响其性能。采用伴随变量法计算优化所需的灵敏度。详细解释了代码,并提供了各种扩展。它分为预优化、MMA优化和后优化操作,每一个操作都是全面详细的。文中还说明了负载灵敏度对优化设计的影响。SoRoTop在“附录A”中提供,并在补充材料中提供扩展,并在https://github.com/PrabhatIn/SoRoTop上公开。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

SoRoTop: a hitchhiker’s guide to topology optimization MATLAB code for design-dependent pneumatic-driven soft robots

SoRoTop: a hitchhiker’s guide to topology optimization MATLAB code for design-dependent pneumatic-driven soft robots

Demands for pneumatic-driven soft robots are constantly rising for various applications. However, they are often designed manually due to the lack of systematic methods. Moreover, design-dependent characteristics of pneumatic actuation pose distinctive challenges. This paper provides a compact MATLAB code, named SoRoTop, and its various extensions for designing pneumatic-driven soft robots using topology optimization. The code uses the method of moving asymptotes as the optimizer and builds upon the approach initially presented in Kumar et al. (Struct Multidiscip Optim 61(4):1637–1655, 2020). The pneumatic load is modeled using Darcy’s law with a conceptualized drainage term. Consistent nodal loads are determined from the resultant pressure field using the conventional finite element approach. The robust formulation is employed, i.e., the eroded and blueprint design descriptions are used. A min–max optimization problem is formulated using the output displacements of the eroded and blueprint designs. A volume constraint is imposed on the blueprint design, while the eroded design is used to apply a conceptualized strain energy constraint. The latter constraint aids in attaining optimized designs that can endure the applied load without compromising their performance. Sensitivities required for optimization are computed using the adjoint-variable method. The code is explained in detail, and various extensions are also presented. It is structured into pre-optimization, MMA optimization, and post-optimization operations, each of which is comprehensively detailed. The paper also illustrates the impact of load sensitivities on the optimized designs. SoRoTop is provided in “Appendix A” and is available with extensions in the supplementary material and publicly at https://github.com/PrabhatIn/SoRoTop.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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