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

基本信息

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

项目摘要

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.

机器人群近年来由于其巨大的潜在应用而引起了很多关注。特别是，对水下游泳或在空气水界面进行冲浪的水生机器人越来越感兴趣。通过使用当地的交流串联工作的大量个人，一群水下游泳者或界面冲浪者可以增强其集体智能，同时保持相对简单的设计。 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这些编队中的机器人。该项目中的计划研究以及一系列教育活动，涉及向中学和高中生推广，与公众的互动，社区学院的指导和研究生的指导以及课程发展。该项目旨在在机器人水流互动中深入了解在机器人运动集体运动中，在机器人运动集体运动中，在机器人运动集体运动中，高级人士和申报人数。为研究选择的机器人的设计是由掌握各自地形的本质中的物种激励的。游泳者模仿一条鱼的一般形式，尾巴拍打提供了推力，而冲浪者则从游动的昆虫中汲取灵感。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机器人之间相对位置的广泛流程和组合。再加上加强学习算法，它们还使搜索集体运动的最佳策略。实验中机器人的运动产生的不稳定流将通过时间分辨的，体积的粒子跟踪速度法捕获。 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.