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.

本项目的目标是发展对控制策略的基本理解，以利用母舰/子舰机器人传感器网络成员在现场执行体积传感的补充计算、传感和通信能力。将网络化无人系统、协作控制、自组织网络受控移动性、运动规划和最优分布式感知的概念结合在一起，创建了一个由两类属性明显不同但具有互补性的机器人组成的新的异质机器人团队。研究活动被组织成三个主要推动力：i)(二)在强流情况下采用有序迎风方法进行运动规划的子代控制，以及在间歇通信情况下采用合作采样的分散复盖控制；2.基于强化学习的母舰控制算法，为子舰的最优部署和重新分配提供容迟联网和随机动态规划；在室内机器人传感器网络、异类无人机系统的室外以及与大气科学家的部分野外活动中进行的实验演示。拟议的研究项目将提供对复杂大气现象的现场体积采样的新能力，这将直接提高理解复杂环境的能力。该项目将通过应用程序产生最广泛的影响，这些应用程序将受益于执行现场科学的机器人传感器网络。合作的重点是研究严重风暴中的龙卷风发生、海冰变化和气团边界的时空演变。此外，研究和教育被纳入旨在改善K-12学生对工程领域的感知的活动中，留住那些最初对工程感兴趣的学生，将实践中的主动学习带到几门空中机器人课程中，并促进科学家和工程研究人员之间的互动。