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

职业：高雷诺数机器人游泳者和冲浪者的集体流体动力学

• 批准号: 2239080
• 负责人: Hassan Masoud
• 金额: $ 52.03万
• 依托单位: Michigan Technological University
• 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: 2022-12-01 至 2027-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2239080&HistoricalAwards=false
• 关键词: CAREER; Collective; Hydrodynamics; Robotic; Swimmers

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.

近年来，机器人群体由于其巨大的潜在应用而引起了人们的广泛关注。特别是，人们对水下机器人越来越感兴趣，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增强他们的集体智慧，同时保持相对简单的设计。利用这种独特的联合能力可以实现上级功能，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，入侵物种的监测，跟踪天气和海洋状况，污染管理，这个项目的主要目标是研究水中机器人有序合奏的流体动力学，并确定集体行为，这些编队中的机器人之间的流动介导的相互作用。本项目的研究内容包括面向中学生、面向公众、社区大学和研究生的指导、课程开发等一系列教育活动。本项目旨在深入了解高雷诺数下机器人游泳者和冲浪者集体运动中的多体流体动力学相互作用。研究中选择的机器人设计的动机是自然界中已经掌握各自地形的物种。游泳者模仿鱼的一般形态，尾巴拍打提供推力，而冲浪者则从水中行走的昆虫中获得灵感。调查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的相对位置的组合。再加上强化学习算法，它们还可以搜索集体运动的最佳策略。实验中机器人运动产生的非定常流将通过时间分辨的体积粒子跟踪测速技术捕获。在这个项目中获得的基本知识预计将直接有助于设计和实现未来的水上机器人，这些机器人能够以高度协调的方式相互配合，这一奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响进行评估来支持审查标准。