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.

从碳纳米管到人尺寸的软机器人，在下一代有希望的工程学科中都存在柔性和可变形的结构。但是，对这些机械系统的仿真通常很慢，并且模拟软件的使用具有挑战性。此外，对于模拟通用机器人研究和教育软件中的柔性结构的支持很少，仅将智能软机器人的使用仅限于专家。另一方面，计算机图形社区开发了高级软件，用于模拟柔性结构，例如头发和毛皮。最近的研究表明，这些计算机图形方法可以准确地模拟软机器人和柔性结构，速度比实时更快。该项目为这些基于物理的灵活结构的模拟开发了一个易于使用的开源软件平台，并将该软件纳入国家网络基础设施生态系统中。所有年龄段的研究人员都可以使用该软件来调查细长结构的机制，软机器人的自主权以及可变形机的突破性设计。这项工作的目的是将离散的差异几何形状（DDG）模拟环境开发为能够广泛提供的软件包装，该软件能够建模软件软件包装软件包装软件包装。 DDG方法可以将细长杆和柔性壳组合成任意形状的低维建模，从而与计算上昂贵的有限元分析（FEA）技术建立了实用但仍然具有物理上准确的对比。这项工作首先开发了一个用于Dismech的核心软件包，该软件包适应了先前的工作以满足国家网络基础设施的标准：可维护，可扩展以及具有强大的用户界面。接下来，通过将Dismech纳入现有的机器人软件套件中来建造，用于宽类柔软和灵活的机器人的虚拟测试床。项目团队将使用合并的软件框架和机器学习方法来制定运动策略，例如软机器人。最后，Dismech的附加组件将将机器学习与基于DDG的物理模型一起使用，以进行更快的模拟，从而证明了该软件在发现潜在的物理现象时的研究潜力。 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 Cyber​​infrastructure in the Directorate for Computer & Information Science & Engineering and the Divisions of Civil, Mechanical and Manufacturing Innovation and Electrical, Communications and该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响评论标准来评估，这是值得支持的。

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