Mechanics of Bioinspired Soft Slender Actuators for Programmable Multimodal Deformation

柔性细长驱动器是一类一维比其他维度大得多的主动结构，在自然界中普遍存在。一般来说，这些结构具有无限多的自由度，这使得它们难以高精度地操纵。有一个迫切需要有效的理论和计算工具，以指导高精度致动器的设计。受象鼻运动的启发，本计画主要研究可程式化多模态驱动下柔性细长驱动器的力学。降维使所提出的模型计算效率高，成本低，鲁棒性，特别是对大变形和逆分析的观点。拟议的活动可以提供机会，将软机器人研究从试错法转变为基于科学的设计策略。这项工作可以作为促进STEM教育的平台。经过验证后，该模型将在开源模拟器中实现，可供软机器人社区的学生，教育工作者和研究人员使用。该模型将为可穿戴设备、柔性电子和手术机器人等各种高精度应用中的软机器人提供新的设计策略。该项目将理论建模、计算力学、材料多物理场、实验力学和机器学习相结合，以解决研究问题。将力学模型和实验验证相结合，建立一个开源的仿真平台，以优化这种致动器的设计。基本的结构是主动细丝理论，利用降维的概念，从一个完全三维的结构，一个积极的基尔霍夫棒，通过描述变形专门通过延伸，曲率和扭转。它将创建一个开源模拟器，并与更广泛的软机器人社区共享。本研究将首先建立一个新的力学理论，以预测柔性细长驱动器末端执行器的轨迹。然后，它可以作为优化末端执行器轨迹的基础。新的理论将通过液晶弹性体纤维的驱动实验进行验证。该项目将涉及理论和实验的同时发展，并将反复修改这两项活动，最终建立一个实验验证的理论和一个最佳的设计模型，具有高预测精度。该奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

Soft slender actuators are active structures that have one dimension much larger than the other dimensions, and are ubiquitous in nature. In general, these structures have an infinite number of degrees of freedom, making them challenging to manipulate with high precision. There is an urgent need for efficient theoretical and computational tools to guide actuator design for high precision actuation. Inspired by elephant-trunk motion, this project fundamentallly investigates the mechanics of soft slender actuators under programmable multimodal actuation. Dimensional reduction makes the proposed model computationally efficient, inexpensive, and robust, especially with a view towards large deformations and inverse analyses. Proposed activties can provide opportunities to transform soft robotic research from a trial-and-error approach to a science-based design strategy. The work can serve as a platform to promote STEM education. After validation, the model will be implemented in an open-source simulator that can be used by students, educators, and researchers in the soft robotics community. The model will inform new design strategies for soft robots in various high-precision applications including wearable devices, flexible electronics, and surgical robotics.This project integrates theoretical modeling, computational mechanics, material multiphysics, experimental mechanics, and machine learning to address the research problem. Mechanics models and experimental validation will be combined to establish an open-source simulation platform to optimize the design of such actuators. The underlying construct is the active filament theory that harnesses the concept of dimensional reduction—from a fully three-dimensional structure to an active Kirchhoff rod—by describing deformation exclusively through extension, curvature, and torsion. It will create an open-source simulator that will be shared with the broader, soft robotics, community . The research will first establish a new mechanics theory to predict the trajectory of the end effector of a soft slender actuator. It can then serve as the foundation to optimize the trajectory of the end effector. The new theory will be validated via experiments through the actuation of liquid crystal elastomer fibers. This project will involve the simultaneous development of theory and experiments and will iteratively revise both activities to ultimately establish an experimentally validated theory and an optimal design model with high predicting accuracy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.