Soft robotics has emerged as a promising technology that holds great potential for various application areas. This is due to soft materials unique properties, including flexibility, safety, and shock absorption, among others. Despite many advancement in the field, the development of effective design methodologies and production techniques for soft robots remains a challenge. Although numerous robot prototypes have been proposed in recent years, their designs are often complex and difficult to produce. As such, there is a need for more efficient and unified design approaches that can facilitate the production of soft robots with desirable properties. In this paper, we propose a method for designing soft robots using elastic beams and spatial compliant mechanisms. The method is based on an evolutionary approach that enables the creation of designs with both high motion and force transmission ratios. Specifically, we focus on the development of locomotion mechanisms using a central linear actuator. Our approach involves the use of commonly available plastic materials and a 3D printer to manufacture the designs. We demonstrate the feasibility of our approach by presenting experimental results that show successful production and real world operation. Overall, our findings suggest that the use of elastic beams and an evolutionary approach can facilitate the creation of soft robots with desirable locomotion properties, including fast locomotion up to 3.7 body lengths per second, locomotion with a payload, and underwater locomotion. This method has the potential to enable the development of more efficient and practical soft robots for various applications.

翻译：软体机器人技术已成为一项前景广阔的技术，在多个应用领域展现出巨大潜力。这得益于软材料独特的性能，包括柔韧性、安全性和减震性等。尽管该领域已取得诸多进展，但开发有效的软体机器人设计方法与制造技术仍面临挑战。近年来虽已提出众多机器人原型，但其设计往往复杂且难以制造。因此，需要更高效统一的设计方法以促进具有理想特性的软体机器人生产。本文提出一种利用弹性梁和空间柔顺机构设计软体机器人的方法。该方法基于进化算法，能够生成具有高运动传动比与力传动比的设计方案。我们特别关注采用中心线性驱动器的运动机构开发。该方法使用常见塑料材料和3D打印机制造设计原型。通过展示成功制造与实际运行的实验结果，我们验证了该方法的可行性。总体而言，研究结果表明：采用弹性梁与进化算法的方法有助于创建具有理想运动特性的软体机器人，包括最高达每秒3.7倍体长的快速运动、负载运动及水下运动能力。该方法有望推动开发适用于多种应用的更高效实用型软体机器人。