RI: Small: Collaborative Research: Micro-Assembly Exploiting SofT RObotics (MAESTRO)

RI：小型：协作研究：微装配开发软机器人 (MAESTRO)

• 批准号: 1619278
• 负责人: Aaron Becker
• 金额: $ 20.13万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1619278&HistoricalAwards=false
• 关键词: RI; Small; Collaborative; Research; Micro

The MAESTRO project will develop a new type of manufacturing by combining soft robotics and swarm control to construct assemblies in 2D and 3D from individual artificial cells made of hydrogels. MAESTRO will design rules for building tiny factories so that, like a conductor?s baton, global control signals will organize artificial cells into complex configurations. These artificial cells can contain living cells and be assembled into tissue for artificial organs, or contain inorganic particles to assemble into micro-scale tools. MAESTRO will ferry desired components in artificial cells constructed from polysaccharide-based hydrogels. Current approaches use engineered structures or live bacteria as micro-scale actuators to push or pull desired objects into place. The proposed approach uses the soft robots themselves as building blocks for desired patterns. The artificial cells excel at encapsulating a wide range of micro and nano-sized particles, for example living cells and magnetic nanoparticles. Furthermore, artificial cells can be triggered to efficiently release their payloads. Novel swarm control algorithms using obstacle-based particle computation will steer the cells. In traditional robotics, simultaneous control of multiple robots is based on individual motion control that requires heterogeneity among robots or the ability to deliver multiple input signals; both approaches are currently impractical in small-scale systems. However, these challenges can be overcome by parallel motion planning in obstacle-filled workspaces. This obstacle-based positional control makes the position of microrobots fully controllable using just a single control input. Actuation of these stimuli-responsive artificial cells in micro-fluidic, obstacle-laden environments presents a paradigm shift in fabrication technology.

MAESTRO项目将开发一种新型的制造方式，将软机器人技术和群体控制相结合，从水凝胶制成的单个人工细胞中构建2D和3D组件。MAESTRO将设计建造小型工厂的规则，这样，就像一个导体？作为指挥棒，全局控制信号将把人工细胞组织成复杂的结构。这些人造细胞可以包含活细胞并组装成人造器官的组织，或者包含无机颗粒以组装成微型工具。MAESTRO将在由多糖基水凝胶构建的人工细胞中运送所需的成分。目前的方法使用工程结构或活细菌作为微尺度致动器，将所需的物体推或拉到位。所提出的方法使用软机器人本身作为所需模式的构建块。人工细胞擅长封装各种微米和纳米尺寸的颗粒，例如活细胞和磁性纳米颗粒。此外，人工细胞可以被触发以有效地释放它们的有效载荷。使用基于障碍物的粒子计算的新型群体控制算法将引导细胞。在传统的机器人技术中，多个机器人的同时控制是基于单独的运动控制，这需要机器人之间的异质性或提供多个输入信号的能力;这两种方法目前在小规模系统中是不切实际的。 然而，这些挑战可以通过在充满障碍物的机器人中进行并行运动规划来克服。这种基于障碍物的位置控制使得微型机器人的位置仅使用单个控制输入就完全可控。在微流体、充满障碍物的环境中致动这些刺激响应性人工细胞呈现了制造技术的范式转变。

项目成果

Exploiting Nonslip Wall Contacts to Position Two Particles Using the Same Control Input

• DOI: 10.1109/tro.2019.2891487
• 发表时间: 2019-02
• 期刊: IEEE Transactions on Robotics
• 影响因子: 7.8
• 作者: Shiva Shahrokhi;Jing-Xin Shi;B. Isichei;Aaron T. Becker

Planning Coordinated Event Observation for Structured Narratives

规划结构化叙事的协调事件观察

• DOI: 10.1109/icra.2019.8794450
• 发表时间: 2019
• 期刊: Planning Coordinated Event Observation for Structured Narratives
• 作者: Shell, Dylan A.;Huang, Li;Becker, Aaron T.;O'Kane, Jason M.
• 通讯作者: O'Kane, Jason M.

Coordinated Particle Relocation with Global Signals and Local Friction (Media Exposition)

通过全局信号和局部摩擦协调粒子重定位（媒体博览会）

• DOI: 10.4230/lipics.socg.2020.72
• 发表时间: 2020
• 期刊: 36th International Symposium on Computational Geometry (SoCG 2020
• 作者: Baez, Victor M.;Becker, Aaron T.;Fekete, S;Schmidt, Arne
• 通讯作者: Schmidt, Arne

Planar Orientation Control and Torque Maximization Using a Swarm With Global Inputs

• DOI: 10.1109/tase.2019.2925908
• 发表时间: 2019-07
• 期刊: IEEE Transactions on Automation Science and Engineering
• 影响因子: 5.6
• 作者: Shiva Shahrokhi;Lillian Lin;Aaron T. Becker

3D Path-Following Using MRAC on a Millimeter-Scale Spiral-Type Magnetic Robot

• DOI: 10.1109/lra.2020.2969159
• 发表时间: 2020-01
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Haoran Zhao;J. Leclerc;Maria Feucht;Olivia Bailey;Aaron T. Becker