用拓扑优化设计气动软夹爪，提升抓取性能并可3D打印。
Soft Pneumatic Grippers: Topology optimization, 3D-printing and Experimental validation
- 基于达西定律建模气压载荷，通过拓扑优化设计柔性结构。
- 2D优化单元在气压下变形更优，3D组装后抓取力更强。
- 适合需要高适应性抓取的机器人场景，如柔性操作。
传统软气动夹爪多依赖经验设计。本文提出系统化拓扑优化框架，将驱动负载的依赖性建模为带排水项的达西定律。以二维柔性臂单元为对象，在气压载荷下作为柔顺机构进行优化。为保证设计鲁棒性和可制造性，采用极小-极大优化，同时考虑蓝图与侵蚀设计的输出变形。对蓝图施加体积约束，对侵蚀部分施加应变能约束。使用移动渐近线法（MMA）求解优化问题。将优化后的二维单元适当拉伸生成三维单元，十个三维单元组装成机械臂。优化后的二维单元及对应夹爪臂在气压加载下均优于传统矩形设计，验证了方法有效性。采用SLA技术打印，对比了不同气压下的数值与实验结果。四个3D打印臂集成支撑结构构成软气动夹爪，可在不同重量、尺寸、结构、刚度和形状的物体上实现抓取操作。
原文摘要 · Abstract (English)
Typically, heuristic/trial-based approaches are used to design soft pneumatic grippers (SPGs). This paper presents a systematic topology optimization framework for developing SPGs. The design-dependent nature of actuating load is modeled using Darcy's law with an added drainage term. A 2D soft arm unit is then optimized as a compliant mechanism under pneumatic loading. To ensure the design is robust and manufacturable, the problem is formulated as a min-max optimization, where output deformations of blueprint and eroded designs are considered. A volume constraint is imposed on the blueprint part, while a strain-energy constraint is enforced on the eroded part. The Method of Moving Asymptotes is employed to solve optimization problems. The optimized 2D part is extruded suitably to generate a 3D unit. Ten such 3D units are assembled to create a gripper arm. Both the optimized 2D unit and the corresponding gripper arm outperform their conventional rectangular designs under pneumatic loading, demonstrating the efficacy of the proposed approach. The arms are fabricated using the SLA printing technique. Numerical and experimental results are compared at different pneumatic loads. Four 3D-printed arms are integrated with a supporting structure to form the SPG. The gripping action of the SPG is demonstrated on objects with different weights, sizes, structures, stiffnesses, and shapes.
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