Topology Design and Optimization of Modular Soft Robots Capable of Homogenous and Heterogenous Reconfiguration
Topology Design and Optimization of Modular Soft Robots Capable of Homogenous and Heterogenous Reconfiguration
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具有同质和异质重构能力的模块化软体机器人的拓扑设计与优化
DOI：
10.1115/1.4062265
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发表时间：
2023
影响因子：
2
通讯作者：
Vikas, Vishesh
中科院分区：
文献类型：
--
作者：
Freeman, Caitlin;Conzola, Justin;Vikas, Vishesh
软材料机器人的可变形性为它们提供了在复杂形状和形式之间转换的能力。这种独特的能力使模块化软机器人（MSoRos）能够组装和重新配置成不同的配置，例如平面和球形。这些拓扑显示了不同的运动模式，这些模式适用于不同的环境，例如，爬行或滚动。本研究提出了在球面和平面构型下均质重构和非均质重构的MSoRos的拓扑设计和优化方法。同构重构是指所有模块都是相同的，而异构重构中包含不相同的模块。顺序设计方法使用多面体（阿基米德或柏拉图）作为基础实体来定义模块特征。由于设计过程涉及非线性投影，基底多面体也决定了重构的类型——非均质（阿基米德）或均质（柏拉图）。然后，应用多面体顶点对齐原理，保证重构过程中模块的几何对齐。定义了平面和球面畸变度量来量化由于重构引起的畸变。然后，通过最小化代价函数（两个失真度量的加权和）来获得最优拓扑。结果是一组MSoRos能够具有不同的1D和2D平面构型（包括非均匀和均匀）和多种不同半径的3D球面构型（包括非均匀和均匀）。该方法在基于立方体（阿基米德体）和立方体和八面体（柏拉图体）组合的MSoRo系统上进行了验证。
The deformability of soft material robots provides them with the ability to transform between complex shapes and forms. This unique ability facilitates Modular Soft Robots (MSoRos) to assemble and reconfigure into different configurations, e.g., planar and spherical. These topologies display widely different locomotion modes that are desirable to navigate different environments, e.g., crawling or rolling for these cases. This research presents topology design and optimization methodology of MSoRos capable of both homogeneous and heterogeneous reconfiguration in spherical and planar configurations. Homogeneous reconfiguration refers to the scenario when all the modules are identical, while the heterogeneous contains nonidentical modules. The sequential design approach uses a polyhedron (Archimedean or Platonic) as the base solid to define module characteristics. As the design processes involve nonlinear projections, the base polyhedron also dictates the type of reconfiguration—heterogeneous (Archimedean) or homogeneous (Platonic). Thereafter, it applies the polyhedron vertex alignment principle to ensure geometric alignment of the modules during reconfiguration. Planar and spherical distortion metrics are defined to quantify distortions due to reconfiguration. Subsequently, the optimal topology is obtained by minimizing a cost function that is a weighted sum of the two distortion metrics. The result is a set of MSoRos capable of distinct 1D and 2D planar configurations (both heterogeneous and homogeneous) and multiple 3D spherical configurations of varying radii (both heterogeneous and homogeneous). The methodology is validated on a MSoRo system based on the combination of a cuboctahedron (Archimedean solid) and a cube and an octahedron (Platonic solids).