CAREER: Guidance and Control of Fish Shoals using Bio-Mimetic Robots

多车辆团队和移动传感器网络的许多控制策略直接源于对动物群体集体行为的数学理解。鱼类的成群、鸟类的成群、群居有蹄类动物的成群，以及人类群体中的交通流动模式，都激发了协调机器人系统的算法。然而，到目前为止，工程与自然之间的关系在很大程度上是单向的。该学院早期职业发展(CALEAR)研究项目致力于通过一项多维研究，通过仿生机器鱼对鱼群进行工程指导和控制，从而“关闭”工程与自然之间的“环路”。这项工作将提高目前对复杂多智能体动态系统的理解，对多车辆机器人学、动物行为科学、水产养殖工程和鱼类保护方法具有潜在的影响。这项职业计划将开发一个全面的动力系统框架，用于研究由活的和仿生的机器鱼组成的鱼群的领导有效性。将调查执行机器人领导权的不同机制，包括复制活的鱼群领导者的关键特征，以及对鱼类种群使用受控刺激，如声音、水流、光和化学物质。将提出分析和控制复杂网络的行为模型和数学方法，以了解和控制鱼群的动态。鱼群导航问题将被描述为加权时变邻近网络上的钉扎控制问题。基于离子聚合物金属复合材料等新兴智能材料，将使用多功能传感器和致动器开发微型机器鱼。这项拟议的研究将与当地一家大型动物水族馆为小学生、初中生和高中生提供的创新教育体验相结合，包括那些来自代表性不足群体的学生。这一经历的目的是激励年轻人在工程和科学领域追求职业生涯。

Many control strategies for multi-vehicle teams and mobile sensor networks directly stem from a mathematical understanding of the collective behavior of animal groups. Schooling of fish, flocking of birds, herding of social ungulates, and patterns of traffic flow in human crowds inspire algorithms for coordinating robotic systems. However, the relationship between engineering and nature has been largely one-directional until now. This Faculty Early Career Development (CAREER) research program aspires to "close the loop" between engineering and nature by a multidimensional study of engineered guidance and control of fish shoals through bio-mimetic robotic fish. This work will improve the current understanding of complex multi-agent dynamical systems, with potential impact on multi-vehicle robotics, animal behavior science, aquacultural engineering, and fish protection methods.This CAREER program will develop a comprehensive dynamical systems framework for studying leadership effectiveness in fish shoals comprising of live and bio-mimetic robotic fish. Different mechanisms for robot leadership enforcement, including the replication of key traits of live shoal leaders and the use of controlled stimuli, such as sound, water flow, light, and chemicals, to the fish population, will be investigated. Behavioral models and mathematical methods for analysis and control of complex networks will be advanced to understand and control the dynamics of fish shoals. The fish shoal guidance problem will be formulated as a pinning control problem over a weighted time-varying proximity network. Miniaturized robotic fish will be developed using multifunctional sensors and actuators based on emerging smart materials, such as ionic polymer metal composites. The proposed research will be integrated with an innovative educational experience at a local large animal aquarium for elementary, middle, and high school students, including those from under-represented groups. The objective of this experience is to inspire young minds in pursuing careers in engineering and sciences.