Robotic See-Through Imaging with Everyday RF Signals

该提案的总体目标是引入一个新的多学科基础，用于使用无人驾驶自动驾驶车辆使用日常RF信号进行透视成像。 使用日常RF信号的透视成像可以显著影响许多不同的领域，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，仅举几例。 另一方面，机器人网络可以在许多不同的领域产生巨大的影响，如救灾，应急响应，环境监测，监视和安全。 这项在RF传感和机器人交叉领域的工作可以通过联合和连续优化机器人路径规划和RF成像来大大推进RF传感的最新技术，从而对我们的社会产生变革性的影响。 该提案还有一个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式，为一些无人驾驶车辆配备使用日常RF信号对完全未知区域进行透视成像。沿着这条线，第一个主要任务集中在运动模式和RF成像性能之间的相互作用，以理解和数学表征机器人的运动模式最有用的RF成像。第二个任务，然后开发的基础上，联合和连续共同设计的路径规划和成像的机器人，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式进行了广泛的验证与地面和空中车辆。总体而言，拟议的研究可以为增强RF成像和机器人技术的最新水平做出重大贡献。

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.