Designing Time-varying Fields to Encode the Autonomous Navigation of Micro-robots

移动的机器人利用其环境的感知信息自主地将其行动导向特定的目标，如货物运送、废物清除或材料修复。 在微观环境中实现类似的目标，例如在人体血管系统内，需要尺寸与活细胞相当的机器人。 然而，所谓的“微型机器人”并不是自主的。 相反，它们需要外部传感器和控制器来指导它们的运动和其他动作。 该项目的目标是创建自主微型机器人，可以在外部监督下导航其环境中的局部变化。 微型机器人是基于小颗粒，可以通过将它们放置在时变磁场中来激励它们。 一旦理解了磁场中粒子的动力学，该项目将设计出引导粒子运动沿着表面形貌（趋地形性）和流体速度（趋流性）梯度的场。除了为研究生和本科生提供研究培训外，该项目还将包括对有兴趣从事STEM领域的高中年轻女性的教育推广。与柯朗研究所的“Girls in STEM”暑期项目合作，微型机器人暑期研究项目将培训学生如何整合数据、模型和设计，以推进工程目标。现有的基于场驱动粒子的微型机器人依赖于对当前位置和目标目的地的了解，控制粒子在流体环境中的运动。这些外部控制策略往往受到有限信息的挑战（即，粒子位置是未知的）和全局激励（即，粒子在公共场中移动）。 该项目将使用三维时变磁场来编码多个粒子的自主导航，以响应粒子环境中的梯度，特别是地形（拓扑性）和速度（趋流性）。重要的是，场并不指示粒子移动到哪里，而是指示粒子如何对环境中的局部变化做出反应。因此，同一个场可以驱动多个粒子同时向不同方向运动。基于模型预测，该项目旨在（1）实验性地展示磁性微粒在复杂地形地貌中的自主导航，（2）通过自动化实验和动力学模型设计改进的驱动协议，以及（3）开发能够在微流体通道内导航速度梯度的趋流性颗粒。这些目标将通过结合时间周期场驱动的磁性微球和椭球体实验以及基于低雷诺数流体动力学的动力学模型来实现，该模型由粒子跟踪数据提供信息和增强。该奖项反映了NSF的法定使命，并被认为值得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来支持。

Mobile robots use sensory information about their environment to direct their actions autonomously toward specific goals such as cargo delivery, waste removal or materials repair. Achieving similar goals in microscopic environments, such as inside the human vascular system, requires robots with dimensions that are comparable to those of living cells. However, so-called “micro-robots” are not autonomous. Instead, they require on external sensor and controllers to direct their motion and other actions. The goal of this project is to create autonomous micro-robots that can navigate local variations in their environment with external supervision. The micro-robots are based on small particles that can be energized by placing them in time-varying magnetic fields. Once the dynamics of the particles in the magnetic field are understood, the project will design fields that direct particle motion along gradients in surface topography (topotaxis) and fluid velocity (rheotaxis). In addition to providing research training for graduate and undergraduate students, the project will include educational outreach to young women in high school interested in pursuing STEM fields. In partnership with the 'Girls in STEM' summer program at the Courant Institute, summer research projects on micro-robotics will train students on the integration of data, models, and design to advance engineering goals.Existing micro-robots based on field-driven particles rely on knowledge of the current position and the target destination to control particle motion through fluid environments. These external control strategies often are challenged by limited information (i.e., particle positions are unknown) and global actuation (i.e., particles move in a common field). This project will use time-varying magnetic fields in three-dimensions to encode the autonomous navigation of multiple particles in response to gradients in the particle environment—particularly, those in topography (topotaxis) and velocity (rheotaxis). Importantly, the field does not instruct particles on where to move but rather on how to respond to local variations in the environment. As a result, the same field can drive multiple particles to move simultaneously in different directions. Building on model predictions, the project aims (1) to demonstrate experimentally the autonomous navigation of magnetic micro-particles across complex topographic landscapes, (2) to design improved driving protocols informed by automated experiments and dynamical models, and (3) to develop rheotactic particles capable of navigating velocity gradients within microfluidic channels. These aims will be achieved through a combination of experiments on magnetic micro-spheres and ellipsoids driven by time-periodic fields and dynamical models based on low Reynolds number hydrodynamics informed and augmented by particle tracking data.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.