Robotics and RF: From X-Ray Vision with WiFi to Communication-Aware Robotics

ECE Seminar: Robotics and RF: From X-Ray Vision with WiFi to Communication-Aware Robotics

Starts at: October 6, 2016 4:30 PM

Ends at: 6:00 PM

Location: 4:30 pm Scaife Hall 125

Speaker: Dr. Yasamin Mostofi

Affiliation: Professor, ECE Department University of California Santa Barbara

Refreshments provided: Yes

Link to Abstract

Link to Video (1)



RF signals are everywhere these days. Can they be used for sensing? Do they carry useful information about the objects they visit? For instance, imagine two unmanned vehicles arriving behind thick concrete walls. They have no prior knowledge of the area behind these walls. But they are able to see every square inch of the invisible area through the walls, fully imaging what is on the other side with high accuracy. Can the robots achieve this with only WiFi signals and no other sensors? In another example, consider the WiFi network of a building. Can it estimate the occupancy level of the building and the spatial concentration of the people, without relying on people to carry a device? In the first part of the talk, I will discuss our latest theoretical and experimental results to achieve these goals. More specifically, I show that it is possible to achieve x-ray vision with only WiFi RSSI signals and image details through thick concrete walls.

Furthermore, I discuss occupancy estimation where I show how to count people with only WiFi measurements. In the second part of the talk, I focus on communication-aware robotics and human-robot networks. I will start by showing how each robot can go beyond the over-simplified but commonly-used disk model for connectivity, and realistically assess the impact of a motion decision on its link quality. By utilizing this framework, I will then show how each unmanned vehicle can best co-optimize its communication, sensing and navigation objectives under resource constraints. This co-optimized approach results in a significant performance improvement as I discuss in the talk. Finally, I show some recent results on human-robot networks that enable the robots to predict human visual performance and incorporate it in their sensing and path planning optimization.


Yasamin Mostofi received her B.S. degree in electrical engineering from Sharif University of Technology, Tehran, Iran, in 1997, and her M.S. and Ph.D. degrees from Stanford University, Stanford, California, in 1999 and 2004, respectively. 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 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. Her research is on mobile sensor networks. Current research thrusts include RF sensing, X-ray vision for robots, communication-aware robotics, human-robot networks, occupancy estimation, and see-through imaging. Her research has appeared in several reputable news outlets such as BBC, Huffington Post, Daily Mail, Engadget, and NSF Science360.