Collaborative Research: Elements: Discrete Simulation of Flexible Structures and Soft Robots

合作研究：元素：柔性结构和软体机器人的离散仿真

• 批准号: 2209782
• 负责人: Mohammad Khalid Jawed
• 金额: $ 34万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2209782&HistoricalAwards=false
• 关键词: Collaborative; Research; Elements; Discrete; Simulation

From carbon nanotubes to human-size soft robots, flexible and deformable structures are present throughout the next generation of promising engineering disciplines. However, simulation of these mechanical systems is often slow, and simulation software is challenging to use. In addition, there is little support for simulating flexible structures in common robotics research and education software, limiting the use of intelligent soft robots to experts only. On the other hand, the computer graphics community has developed advanced software for simulating flexible structures like hair and fur. Recent research has shown these computer graphics approaches can accurately simulate soft robots and flexible structures faster than real-time. This project develops an easy-to-use open-source software platform for these fast physics-based simulations of flexible structures, and incorporates the software into the national cyberinfrastructure ecosystem. This software, DiSMech, can be used by researchers of all ages to investigate the mechanics of slender structures, autonomy for soft robots, and breakthrough designs for deformable machines.The objective of this work is to develop a discrete differential geometry (DDG) simulation environment into a widely-available software package capable of modeling soft and flexible structures. The DDG approach enables low-dimensional modeling of slender rods and flexible shells combined into arbitrary shapes, establishing a practical but still physically accurate contrast to computationally expensive finite element analysis (FEA) techniques. This work first develops a core software package for DiSMech that adapts prior work to meet the standard for national cyberinfrastructure: maintainable, extensible, and with a robust user interface. Next, a virtual testbed for a wide class of soft and flexible robots is built by incorporating DiSMech into an existing robotics software suite. The project team will use the combined software framework with a machine learning approach to develop a locomotion strategy for example soft robots. Finally, add-ons to DiSMech will incorporate machine learning alongside the DDG-based physics models for even faster simulations, demonstrating the research potential for this software in uncovering underlying physical phenomena. By advancing DDG-based physics simulations to capture a wide range of soft and flexible structures, with a computational speed sufficient for learned robot control, all in an easy-to-use interface, DiSMech addresses an important gap in the national cyberinfrastructure.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer & Information Science & Engineering and the Divisions of Civil, Mechanical and Manufacturing Innovation and Electrical, Communications and Cyber Systems in the Directorate of Engineering.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.

从碳纳米管到人类大小的软体机器人，柔性和可变形的结构出现在下一代有前途的工程学科中。然而，这些机械系统的仿真通常是缓慢的，仿真软件是具有挑战性的使用。此外，在常见的机器人研究和教育软件中，很少支持模拟柔性结构，限制了智能软机器人的使用，只有专家才能使用。另一方面，计算机图形界已经开发出先进的软件来模拟像头发和毛皮这样的柔性结构。最近的研究表明，这些计算机图形学方法可以比实时更快地精确模拟软机器人和柔性结构。该项目开发了一个易于使用的开源软件平台，用于这些快速的基于物理的柔性结构模拟，并将该软件纳入国家网络基础设施生态系统。这个软件，DiSMech，可以被所有年龄的研究人员用来研究细长结构的力学，软机器人的自主性，以及可变形机器的突破性设计。这项工作的目标是将一个离散微分几何（DDG）仿真环境开发成一个广泛可用的软件包，能够对软性和柔性结构进行建模。DDG方法可以对任意形状的细长杆和柔性壳进行低维建模，与计算成本高昂的有限元分析（FEA）技术相比，建立了实用但物理上仍然准确的对比。这项工作首先为DiSMech开发了一个核心软件包，该软件包对之前的工作进行了调整，以满足国家网络基础设施的标准：可维护、可扩展和具有强大的用户界面。接下来，通过将DiSMech整合到现有的机器人软件套件中，构建了一个用于各种软柔性机器人的虚拟测试平台。项目团队将使用结合了机器学习方法的软件框架来开发运动策略，例如软机器人。最后，DiSMech的附加组件将结合机器学习和基于ddg的物理模型，以实现更快的模拟，展示了该软件在揭示潜在物理现象方面的研究潜力。通过推进基于ddg的物理模拟来捕获广泛的柔软和柔性结构，其计算速度足以用于学习机器人控制，所有这些都在一个易于使用的界面中，DiSMech解决了国家网络基础设施的一个重要空白。该项目由计算机与信息科学与工程理事会的先进网络基础设施办公室以及工程理事会的土木、机械和制造创新以及电气、通信和网络系统部门提供支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Design of Bistable Soft Deployable Structures via a Kirigami‐Inspired Planar Fabrication Approach

• DOI: 10.1002/admt.202300088
• 发表时间: 2023-01
• 期刊: Advanced Materials Technologies
• 影响因子: 6.8
• 作者: Mrunmayi Mungekar;Leixin Ma;Wenzhong Yan;Vishal Kackar;Shyan Shokrazadeh;M. Jawed

mBEST: Realtime Deformable Linear Object Detection Through Minimal Bending Energy Skeleton Pixel Traversals

mBEST：通过最小弯曲能量骨架像素遍历进行实时可变形线性物体检测

• DOI: 10.1109/lra.2023.3290419
• 发表时间: 2023
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Choi, Andrew;Tong, Dezhong;Park, Brian;Terzopoulos, Demetri;Joo, Jungseock;Jawed, Mohammad Khalid
• 通讯作者: Jawed, Mohammad Khalid