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Robotic See-Through Imaging with Everyday RF Signals

使用日常射频信号进行机器人透视成像

基本信息

批准号：
1611254
负责人：
Yasamin Mostofi
金额：
$ 30万
依托单位：
University of California-Santa Barbara
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2020-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1611254&HistoricalAwards=false
关键词：
Robotic See Through Imaging Everyday

项目摘要

The overall goal of this proposal is to introduce a new multi-disciplinary foundation for see-through imaging with everyday RF signals using unmanned autonomous vehicles. See-through imaging with everyday RF signals can considerably impact many different areas such as search and rescue operations, surveillance and security, detection/classification of occluded objects, infrastructure assessment, medical imaging, and archaeological exploration, just to name a few. Robotic networks, on the other hand, can have a tremendous impact in many different areas such as disaster relief, emergency response, environmental monitoring, surveillance, and security. This proposed work at the intersection of RF sensing and robotics can considerably advance the state-of-the-art in RF sensing by jointly and successively optimizing robotic path planning and RF imaging, and can thus have a transformative impact on our society. The proposal also has a significant educational component targeting under-represented students. More specifically, in this research effort, a new multi-disciplinary paradigm is proposed to equip a number of unmanned vehicles with see-through imaging of completely unknown areas using everyday RF signals. Along this line, the first major task focuses on the interplay between motion patterns and RF imaging performance, in order to understand and mathematically characterize robotic motion patterns most informative for RF imaging. The second task then develops the foundation of jointly and successively co-designing the path planning and imaging of the robots while considering the dynamics of the vehicles, environmental navigation constraints, motion energy budget, and operation time. Finally, the proposed theories and design paradigm are extensively validated with ground and aerial vehicles. Overall, the proposed research can make a significant contribution to enhancing the state-of-the-art in both RF imaging and robotics.

该提案的总体目标是引入一个新的多学科基础，用于使用无人驾驶车辆对日常射频信号进行透视成像。使用日常射频信号进行透视成像可以极大地影响许多不同领域，例如搜索和救援行动、监视和安全、遮挡物体的检测/分类、基础设施评估、医学成像和考古勘探等等。另一方面，机器人网络可以在救灾、应急响应、环境监测、监视和安全等许多不同领域产生巨大影响。这项在射频传感和机器人技术交叉领域提出的工作可以通过联合和连续优化机器人路径规划和射频成像来显着推进射频传感领域的最先进技术，从而对我们的社会产生变革性影响。该提案还包含针对代表性不足的学生的重要教育内容。更具体地说，在这项研究工作中，提出了一种新的多学科范例，为许多无人驾驶车辆配备使用日常射频信号对完全未知区域进行透视成像的技术。沿着这条线，第一个主要任务侧重于运动模式和射频成像性能之间的相互作用，以便理解和数学表征对于射频成像最有信息的机器人运动模式。然后，第二项任务为联合连续设计机器人的路径规划和成像奠定基础，同时考虑车辆的动力学、环境导航约束、运动能量预算和操作时间。最后，所提出的理论和设计范例在地面和飞行器上得到了广泛的验证。总体而言，拟议的研究可以为提高射频成像和机器人技术的最新水平做出重大贡献。