Robotic See-Through Imaging with Everyday RF Signals

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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.