Unless otherwise noted, all seminars will take place in the 6th floor conference room of Donald Bren Hall (DBH 6011). Refreshments will be served at 10:50am, and the seminar talks will run from 11:00am until noon.
For additional information, please contact CS Seminar Administrative Coordinator, Mare Stasik, at email@example.com or (949) 824-7651.
June 7, 2019
11:00am - 12:00pm
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.