Energy-Efficient, Multi-Scale, Biologically-Inspired Mobile Sensor Networks with Real-Time Observation Adaptability

具有实时观测适应性的节能、多尺度、受生物启发的移动传感器网络这一集成系统方案的重点是水动力耦合仿生水下航行器的协同推进。该平台的优势在于将流量传感集成到车辆-尾迹相互作用的闭环控制中。一个像鱼一样的机器人将被制造出来，通过分布在车辆两侧的微型机械毛细胞来实时响应周围的流量。将开发计算多尺度算法，以便从传感器数据中快速提取相关流量信息。将推导出分析和计算模型，阐明鱼类利用环境水流进行有效游泳的原理，重点关注鱼群行为。这些原理将用于设计反馈控制律，使机器人在非定常流动中高效运动。然后将开发快速近似动态规划算法，用于车辆学校的重定向和重塑，以最大限度地从时变来源收集信息。提出的研究的智力价值在于创造分析和计算工具和技术，使车辆学校能够利用非定常流原理来实现节能运动和自适应传感机动。这项研究的广泛影响是为自主移动传感器阵列提供了基础，这些传感器阵列可以在前所未有的距离上部署，用于从环境采样到军事情报收集的水下应用。该项目还将加强UIUC的跨学科工程课程，并直接培养一名博士生和多名本科生。

ECS-0501407Energy-Efficient, Multi-Scale, Biologically-Inspired Mobile Sensor Networks with Real-Time Observation AdaptabilityThis integrative systems proposal focuses on the cooperative propulsion of hydrodynamically-coupled biomimetic underwater vehicles. The superiority of the proposed platform hinges on the integration of flow sensing into the closed-loop control of vehicle-wake interactions. A fish-like robot will be constructed that responds in real time to ambient flows estimated using micro-machined hair cells distributed along the vehicle's sides. Computational multi-scale algorithms will be developed to enable the rapid extraction of relevant flow information from sensor data. Analytical and computational models will be derived to clarify the principles by which fish exploit ambient flows for efficient swimming, focusing on schooling behavior. These principles will be used to design feedback control laws for efficient robotic locomotion through unsteady flows. Fast approximate dynamic programming algorithms will then be developed for the redirection and reshaping of vehicle schools to maximize the collection of information from time-varying sources. The intellectual merit of the research proposed is in creating analytical and computational tools and technology that will enable schools of vehicles to exploit principles of unsteady flow to achieve energy efficient locomotion and maneuvering for adaptive sensing.The broad impact of the research is in providing the basis for autonomous mobile sensor arrays to be deployed over unprecedented distances for underwater applications ranging from environmental sampling to the collection of military intelligence. This project will also enhance the interdisciplinary engineering curriculum at UIUC and directly train one PhD student and numerous undergraduates.