ITR - (NHS+ASE+ECS) - (dmc+sim+int): Loosely Cooperating Micro Air Vehicle Networks for Toxic Plume Characterization

提案编号：0427947PI：卡姆兰·莫塞尼研究所：科罗拉多大学，博尔德标题：ITR-松散合作的微型飞行器网络有毒羽流特征摘要：城市地区污染物的释放会导致严重的公共健康后果。该项目开发了一个集成的传感器群，以实现对有毒羽流的快速表征，以进行污染预测和来源定位。传感器群由半自动微型飞行器(MAV)组成，在人口稠密地区上空的大气层中运送微型毒素传感器，并与基站联网，使用新型的轻型、实时、数据反应型无线信息路由提供毒素扩散建模和群群监控。MAV平台降低了制造成本，降低了碰撞损坏的风险，并降低了可能引起公众警报的能见度和噪音。引入信息能量的概念是为了紧密结合三个跨学科领域的进展：空气动力学、网络和控制。这使得传感器群能够使用相对简单的个人车辆来提供高质量的信息产品。小牛是根据蝙蝠飞行的仿生原理设计的，以实现卓越的飞行性能。车辆控制基于分层的信息能量公式，在每辆车上产生简单的梯度下降制导规律，但具有众所周知的针对高质量数据区域的群聚类行为。研究了数据驱动的路由在以下三种通信场景中的行为：MAV间交换高质量数据以实现集群收敛；MAV对地收集传感器数据；以及MAV对地指挥和控制。CU Boulder现有的学科课程丰富了这项工作的成果，扩大了学生对多学科的接触。暑期航空机器人项目使当地高中生能够参加计算机科学和航空航天工程相结合的设计/建造/飞行比赛。

Proposal Number: 0427947PI: Kamran Mohseni Institution: University of Colorado, Boulder Title: ITR - Loosely Cooperating Micro Air Vehicle Networks for Toxic Plume CharacterizationAbstract: Release of contaminants in urban areas can lead to severe public health consequences. This project develops an integrated Sensor Flock to enable rapid characterization of toxic plumes for contamination prediction and source location. A Sensor Flock consists of semi-autonomous micro air vehicles (MAVs) transporting miniature toxin sensors throughout the atmosphere above populated areas, networked to a base station providing toxin dispersion modeling and flock supervision, using novel lightweight, real-time, data-reactive wireless information routing. MAV platforms lower manufacturing costs, reduce risks of collision damage, and reduce visibility and noise that might create public alarm. The concept of Information Energy is introduced to tightly integrate advances in three interdisciplinary areas: aerodynamics, networking, and control. This enables high-quality information products from the Sensor Flock, using relatively simple individual vehicles. The MAVs are designed based on biomimetic principles of bat flight to enable exceptional flight performance. Vehicle control is based on a hierarchical information energy formulation, producing simple gradient-descent guidance laws on each vehicle, but with well-understood flock clustering behavior toward regions of high-quality data. The behavior of data-driven routing in each of the following three communication scenarios is investigated: inter-MAV exchange of high-quality data for flock convergence; MAV-to-ground collection of sensor data; and ground-to-MAV command and control. Existing disciplinary courses at CU Boulder are enriched with results from this work, expanding student multidisciplinary exposure. A summer Aerobotics program enables local high school students to participate in a design/build/fly competition integrating computer science and aerospace engineering.