CAREER: Collective Hydrodynamics of Robotic Swimmers and Surfers at High Reynolds Numbers

近年来，机器人群因其巨大的应用潜力而引起了广泛的关注。特别是，人们对水生机器人的兴趣越来越大，无论是在水下游泳还是在空气-水界面冲浪。通过使用大量的个体通过本地通信协同工作，一群水下游泳者或界面冲浪者可以在保持相对简单的设计的同时增强他们的集体智慧。利用这种独特的联合能力可以实现优越的功能，这使得水生机器人在无数的实际应用中非常有吸引力，包括监视，监测入侵物种，跟踪天气和海况，污染管理等。该项目的主要目标是研究有序整体运动的水生机器人的流体动力学，并确定这些编队中机器人之间流动介导的相互作用所产生的集体行为。本项目计划的研究与一系列教育活动相结合，包括向中学生和高中生推广，与公众接触，社区大学和研究生的指导，以及课程开发。该项目旨在深入了解机器人游泳者和冲浪者在高雷诺数下集体运动中的多体水动力相互作用。研究中选择的机器人的设计灵感来自于自然界中已经掌握了各自地形的物种。游泳者模仿鱼的一般形态，用尾巴拍打提供推力，而冲浪者则从水中行走的昆虫那里获得灵感。研究将使用高保真数值模拟和实验室实验的协同应用进行。经过验证的模拟允许探索广泛的流动状态和机器人之间相对位置的组合。与强化学习算法相结合，它们还可以搜索集体运动的最佳策略。实验中由机器人运动产生的非定常流将通过时间分辨、体积粒子跟踪测速法捕获。在这个项目中获得的基本知识预计将直接有助于未来水生机器人的设计和实现，这些机器人能够以高度协调的方式相互协作，类似于鱼群和鸟群所表现出的行为。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。

Robotic swarms have attracted much attention in recent years due to their vast potential applications. In particular, there has been a growing interest in aquatic robots, either swimming underwater or surfing at the air-water interface. By using large numbers of individuals working in tandem through local communication, a swarm of underwater swimmers or interfacial surfers can augment their collective intelligence while maintaining relatively simplistic designs. Harnessing this unique, joint ability leads to achieving superior functionalities, which makes aquatic robots very appealing for a myriad of practical applications, including surveillance, monitoring of invasive species, tracking weather and sea conditions, pollution management, etc. The principal objective of this project is to examine the hydrodynamics of aquatic robots locomoting in orderly ensembles and to identify the collective behaviors that emerge from the flow-mediated interactions among the robots in those formations. The planned research studies in this project are coupled with a range of educational activities that involve outreach to middle and high school students, engagement with the general public, mentorship of community college and graduate students, and curriculum development.This project aims to obtain an in-depth understanding of many-body hydrodynamic interactions in the collective motion of robotic swimmers and surfers at high Reynolds numbers. The design of robots chosen for the studies is motivated by species in nature that have mastered their respective terrains. The swimmers mimic the general form of a fish, with the tail flapping providing the thrust, while the surfers take inspiration from water-walking insects. The investigations will be conducted using a synergistic application of high-fidelity numerical simulations and laboratory experiments. Validated simulations allow for exploring an extensive range of flow regimes and combinations of relative positions between the robots. Coupled with reinforcement learning algorithms, they also enable searching for optimal strategies for collective locomotion. The unsteady flows generated by the motion of robots in the experiments will be captured via time-resolved, volumetric particle tracking velocimetry. The fundamental knowledge gained during this project is expected to directly contribute to the design and implementation of future aquatic robots capable of functioning alongside each other with a high degree of coordination, similar to the behaviors exhibited by fish in schools and birds in flocks.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.