EFRI C3 SoRo: Programmable Skins for Moldable and Morphogenetic Soft Robots

EFRI C3 SoRo：用于可塑和形态生成软机器人的可编程皮肤

• 批准号: 1830870
• 负责人: Rebecca Kramer-Bottiglio
• 金额: $ 200万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830870&HistoricalAwards=false
• 关键词: EFRI; C3; SoRo; Programmable; Skins

This project seeks to address the problem of preparing a robot to perform a set of known tasks, despite the lack of any information about the task to be performed or the environment in which it occurs. The approach taken is to construct an active robotic skin, integrating motion, sensing, and decision-making into a single conformable material skin with embedded sensors and actuators, and wrap it around a passive, moldable core material. The skin acts to deform the core, in such a way as to make the robot move, in a manner which is optimized for its surroundings using evolutionary algorithms. In preliminary work, the PI team has demonstrated an initially spherical robot first causing itself to roll, and then morphing to a cylinder and switching to an inchworm-type gait. This project will leverage novel insights from biological systems to derive new operational principles for robots capable of editing their own algorithmic control structure to make use of a changing anatomy, enabling more robust functionality. The results of this research will enable morphing robots that can adjust their morphology to accomplish different tasks or move more efficiently to meet the demands of changing environments or contexts. This project addresses the producing of a transformative tool that can adapt for exploration or discovery of unknown, dangerous, or unpredictable environments. Rigid-bodied robots generally excel at specific tasks in structured environments, but lack the versatility and adaptability required to interact-with and locomote-within the natural world. This project will introduce robotic skins that wrap around arbitrary soft bodies to induce the desired motions and deformations. With the addition of robotic skins, passive soft bodies may be turned into active soft robots. Robotic skins integrate actuation, sensing, variable stiffness, and computation into a single conformable material, and may be leveraged to create morphing robots capable of editing their own morphology and control in unstructured and dynamic environments. The objective of the proposed work is to develop and implement an end-to-end procedure that begins with behavior specifications and ends with a physical self-morphing soft robot and its software environment. The approach will employ robotic skins as the foundation of morphing machines by wrapping them around moldable materials (e.g. clay), enabling surface-driven shape change. Robotic skins will mold the underlying body into a desired shape through controlled surface strains, surface pressures and selective stiffening. As the environment or task changes, the skin will re-mold the body into a new shape that is optimized for its context. This approach will leverage novel insights from diverse biological systems to derive new mathematical models, evolutionary algorithms, and multifunctional materials to enable unparalleled contextually-sensitive morphing capabilities for soft robots.This project is jointly sponsored by the National Science Foundation, Office of Emerging Frontiers and Multidisciplinary Activities (EFMA) and the US Air Force Office of Scientific Research (AFOSR).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.

该项目旨在解决准备机器人执行一组已知任务的问题，尽管缺乏有关要执行的任务或发生的环境的任何信息。所采取的方法是构建一个主动机器人皮肤，将运动、传感和决策集成到一个具有嵌入式传感器和致动器的单一适形材料皮肤中，并将其包裹在一个被动的、可模制的核心材料周围。皮肤的作用是使核心变形，从而使机器人移动，其方式是使用进化算法对其周围环境进行优化。在初步工作中，PI团队已经展示了一个最初的球形机器人，首先使自己滚动，然后变形为圆柱体并切换到尺蠖式步态。该项目将利用生物系统的新见解，为能够编辑自己的算法控制结构的机器人推导新的操作原理，以利用不断变化的解剖结构，实现更强大的功能。这项研究的结果将使变形机器人能够调整其形态来完成不同的任务或更有效地移动，以满足不断变化的环境或上下文的需求。该项目旨在开发一种变革性工具，可以适应未知，危险或不可预测的环境的探索或发现。 刚体机器人通常擅长于结构化环境中的特定任务，但缺乏与自然世界互动和运动所需的多功能性和适应性。这个项目将介绍机器人皮肤，包裹在任意柔软的身体，以诱导所需的运动和变形。随着机器人皮肤的增加，被动软体可以变成主动软体机器人。机器人皮肤将致动、感测、可变刚度和计算集成到单个适形材料中，并且可以被利用来创建能够在非结构化和动态环境中编辑它们自己的形态和控制的变形机器人。拟议工作的目标是开发和实现一个端到端程序，该程序从行为规范开始，以物理自变形软机器人及其软件环境结束。该方法将采用机器人皮肤作为变形机器的基础，通过将它们包裹在可模制材料（例如粘土）周围，实现表面驱动的形状变化。机器人皮肤将通过控制表面应变、表面压力和选择性硬化将底层身体塑造成所需的形状。随着环境或任务的变化，皮肤将重新塑造身体成为一个新的形状，这是优化其上下文。该方法将利用来自不同生物系统的新颖见解来推导新的数学模型，进化算法和多功能材料，以实现软机器人无与伦比的上下文敏感变形能力。该项目由美国国家科学基金会，新兴前沿和多学科活动办公室（EFMA）和美国空军科学研究办公室（AFOSR）该奖项反映了NSF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

Reprogrammable soft actuation and shape-shifting via tensile jamming

• DOI: 10.1126/sciadv.abh2073
• 发表时间: 2021-10
• 期刊: Science Advances
• 影响因子: 13.6
• 作者: Bilige Yang;Robert L. Baines;Dylan S. Shah;Sreekalyan Patiballa;E. Thomas;M. Venkadesan;Rebecca Kramer‐Bottiglio

Robotic Skins With Integrated Actuation, Sensing, and Variable Stiffness

具有集成驱动、传感和可变刚度的机器人皮肤

• DOI: 10.1109/lra.2023.3337702
• 发表时间: 2024
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Shah, Dylan S.;Woodman, Stephanie J.;Buckner, Trevor L.;Yang, Ellen J.;Kramer-Bottiglio, Rebecca K.
• 通讯作者: Kramer-Bottiglio, Rebecca K.

Scale invariant robot behavior with fractals

具有分形的尺度不变机器人行为

• DOI: 10.15607/rss.2021.xvii.059
• 发表时间: 2021
• 期刊: Proceedings of Robotics: Science and Systems
• 作者: Kriegman, Sam;Mohammadi Nasab, Amir;Blackiston, Douglas;Steele, Hannah;Levin, Michael;Kramer-Bottiglio, Rebecca;Bongard, Josh
• 通讯作者: Bongard, Josh

Morphing Robots Using Robotic Skins That Sculpt Clay

使用可雕刻粘土的机器人皮肤来变形机器人

• DOI: 10.1109/lra.2019.2902019
• 发表时间: 2019
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Shah, Dylan S.;Yuen, Michelle C.;Tilton, Liana G.;Yang, Ellen J.;Kramer-Bottiglio, Rebecca
• 通讯作者: Kramer-Bottiglio, Rebecca

Selecting continuous life-like cellular automata for halting unpredictability: evolving for abiogenesis

选择连续的栩栩如生的细胞自动机来阻止不可预测性：自然发生的进化

• DOI: 10.1145/3520304.3529037
• 发表时间: 2022
• 期刊: Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '22
• 作者: Davis, Q. Tyrell;Bongard, Josh
• 通讯作者: Bongard, Josh