CAREER: Mothership/Daughtership Architectures for In Situ Science by Robotic Sensor Networks

职业：机器人传感器网络用于原位科学的母舰/子舰架构

• 批准号: 0845835
• 负责人: Eric Frew
• 金额: $ 49.86万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0845835&HistoricalAwards=false
• 关键词: CAREER; Mothership; Daughtership; Architectures; Situ

The objective of this project is to develop fundamental understanding of control strategies that can exploit the complimentary computation, sensing, and communication capabilities of the members of a mothership/daughtership robotic sensor network performing in situ volumetric sensing. Concepts from networked unmanned systems, cooperative control, controlled mobility in ad hoc networks, motion planning, and optimal distributed sensing are combined to create a new heterogeneous robot team comprised of two classes of robots with significantly different, though complementary, attributes. Research activities are organized into three main thrusts: i.) daughtership control using ordered upwind methods for motion planning in the presence of strong currents and decentralized coverage control for cooperative sampling in the presence of intermittent communication; ii.) mothership control algorithms based on reinforcement learning to provide delay-tolerant networking and stochastic dynamic programming for optimal deployment and reassignment of the daughterships; and iii.) experimental demonstration performed on an indoor robotic sensor network, outdoors on a heterogeneous unmanned aircraft system, and part of field campaigns with atmospheric scientists.The proposed research project will provide new capabilities for in situ volumetric sampling of complex atmospheric phenomena which will lead to a direct improvement in the ability to understand complex environments. This project will have its broadest impact through the applications that will benefit from robotic sensor networks performing in situ science. Collaborations focus on the study of tornadogenesis in severe storms, sea ice change, and spatio-temporal evolution of airmass boundaries. Additionally, research and education are integrated into activities aimed at improving the perception of the engineering field by K-12 students, retaining those students who are initially attracted to engineering, bringing hands-on active learning to several aerial robotic courses, and fostering interaction between scientists and engineering researchers.

该项目的目标是发展对控制策略的基本理解，这些策略可以利用执行原位体积传感的母船/子船机器人传感器网络成员的互补计算、传感和通信能力。来自网络无人系统、协作控制、自组织网络中的受控移动性、运动规划和最佳分布式传感的概念相结合，创建了一个新的异构机器人团队，该团队由两类具有显着不同但互补属性的机器人组成。研究活动分为三个主要方向：i.）在存在强流的情况下使用有序逆风方法进行运动规划的子群控制，以及在存在间歇通信的情况下使用分散覆盖控制进行合作采样； ii.) 基于强化学习的母舰控制算法，提供延迟容忍网络和随机动态规划，以实现子舰的最佳部署和重新分配； iii.) 在室内机器人传感器网络、室外异构无人机系统上进行的实验演示，以及与大气科学家合作的部分现场活动。拟议的研究项目将为复杂大气现象的原位体积采样提供新的功能，这将导致理解复杂环境的能力的直接提高。该项目将通过受益于机器人传感器网络执行原位科学的应用产生最广泛的影响。合作重点是研究强风暴中的龙卷风、海冰变化和气团边界的时空演化。此外，研究和教育被融入到旨在提高 K-12 学生对工程领域的认知的活动中，留住那些最初对工程感兴趣的学生，为一些空中机器人课程带来实践主动学习，并促进学生之间的互动。科学家和工程研究人员。