Recent years have seen a great progress in the area of robotics. Communication signals are also ubiquitous these days. In this talk, I will explore the opportunities and challenges at this intersection, for sensing and communication. In the first part of the talk, I will focus on robotic sensing, and ask the following question “Can everyday communication signals, such as WiFi signals, give new sensing capabilities to unmanned vehicles?” For instance, imagine two unmanned vehicles arriving behind thick concrete walls. Can they image every square inch of the invisible area through the walls with only WiFi signals? I will show that this is indeed possible, and discuss how our methodology for the co-optimization of path planning and communication has enabled the first demonstration of 3D imaging through walls with only drones and WiFi. I will also discuss other new RF sensing capabilities that have emerged from our approach, such as the first demonstration of through-wall crowd counting and occupancy analytics with only WiFi signals, without relying on people to carry a device.
In the second part of the talk, I will focus on communication-aware robotics, a term coined to refer to robotic systems that explicitly take communication issues into account in their decision making. This is an emerging area of research that not only allows a team of unmanned vehicles to attain the desired connectivity during their operation, but can also extend the connectivity of the existing communication systems through the use of mobility. I will then discuss our latest theoretical and experimental results along this line. I will show how each robot can go beyond the over-simplified but commonly-used disk model for connectivity, and realistically model the impact of channel uncertainty for the purpose of path planning. I will then show how the unmanned vehicles can properly co-optimize their communication, sensing and navigation objectives under resource constraints. This co-optimized approach can result in a significant performance improvement and resource saving, as we shall see. I will also discuss the role of human collaboration in these networks.
Yasamin Mostofi received the B.S. degree in electrical engineering from Sharif University of Technology, and the M.S. and Ph.D. degrees from Stanford University. She is currently a professor in the Department of Electrical and Computer Engineering at the University of California Santa Barbara. Yasamin is the recipient of the 2016 Antonio Ruberti Prize from the IEEE Control Systems Society, the Presidential Early Career Award for Scientists and Engineers (PECASE), the National Science Foundation (NSF) CAREER award, and the IEEE 2012 Outstanding Engineer Award of Region 6 (more than 10 Western U.S. states), among other awards. She was a semi-plenary speaker at the 2018 IEEE Conference on Decision and Control (CDC) and a keynote speaker at the 2018 Mediterranean Conference on Control and Automation (MED). Her research is at the intersection of the two areas of robotics and communications, on mobile sensor networks. Current research thrusts include X-ray vision for robots, see-through imaging, RF sensing, occupancy analytics with everyday communication signals, communication-aware robotics, and human-robot networks. Her research has appeared in several reputable news venues such as BBC, Huffington Post, Daily Mail, Engadget, TechCrunch, NSF Science360, ACM News, and IEEE Spectrum, among others.