Jiang Pei, Ma Teng, Luo Ji, Yang Yang, Yin Chao, Zhong Yong
State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China.
School of Automation, Nanjing University of Information Science and Technology, Nanjing, China.
Soft Robot. 2025 Feb;12(1):68-80. doi: 10.1089/soro.2024.0040. Epub 2024 Aug 14.
Due to their exceptional adaptability, inherent compliance, and high flexibility, soft actuators have significant advantages over traditional rigid actuators in human-machine interaction and in grasping irregular or fragile objects. Most existing soft actuators are designed using preprogramming methods, which schedule complex motions into flexible structures by correctly designing deformation constraints. These constraints restrict undesired deformation, allowing the actuator to achieve the preprogrammed motion when stimulated. Therefore, these actuators can only achieve a certain type of motion, such as extension, bending, or twisting, since it is impossible to adjust the deformation constraints once they are embedded into the structures. In this study, we propose the use of variable stiffness materials, such as shape memory polymer (SMP), in the structural design of soft actuators to achieve variable stiffness constraints. A reconfigurable soft helical actuator with a variable stiffness skeleton is developed based on this concept. The skeleton, made of SMP, is encased at the bottom of a fiber-reinforced chamber. In its high-stiffness state, the SMP constrains the deformation toward the skeleton when the actuator is pressurized. This constraint is removed once the SMP skeleton is heated, endowing the actuator with the ability to switch between bending and helical motion in real-time. A theoretical model is proposed to predict the behavior of the actuator when driven by pressure, and experiments are conducted to verify the model's accuracy. In addition, the influence of different design parameters is investigated based on experimental results, providing reference guidelines for the design of the actuator.
由于其卓越的适应性、固有的柔顺性和高灵活性，软驱动器在人机交互以及抓取不规则或易碎物体方面比传统刚性驱动器具有显著优势。大多数现有的软驱动器是采用预编程方法设计的，即通过正确设计变形约束将复杂运动规划到柔性结构中。这些约束限制了不期望的变形，使驱动器在受到刺激时能够实现预编程的运动。因此，这些驱动器只能实现某一种类型的运动，如伸展、弯曲或扭转，因为一旦变形约束嵌入到结构中就无法调整。在本研究中，我们建议在软驱动器的结构设计中使用可变刚度材料，如形状记忆聚合物（SMP），以实现可变刚度约束。基于这一概念开发了一种具有可变刚度骨架的可重构软螺旋驱动器。由SMP制成的骨架封装在纤维增强腔室的底部。在其高刚度状态下，当驱动器受压时，SMP会将变形约束向骨架方向。一旦SMP骨架被加热，这种约束就会消除，使驱动器能够实时在弯曲和螺旋运动之间切换。提出了一个理论模型来预测驱动器在压力驱动下的行为，并进行了实验以验证模型的准确性。此外，基于实验结果研究了不同设计参数的影响，为驱动器的设计提供了参考指导。
