In this talk I will present the seeing-eye robot grand challenge and discuss the components required to design and build a service robot that can replace most, if not all, functionalities of a seeing-eye dog. This challenge encompasses a variety of research problems that can benefit from human-inspired AI: reasoning about other agents, human-robot interactions, explainability, teaching teammates, and more. For each of these problems, I will present an example novel contribution that leverages the bilateral investigation of human and artificial intelligence. Finally, I will discuss the many remaining challenges towards achieving a seeing-eye robot and how I plan to tackle these challenges.
Reuth Mirsky is a Postdoctoral Fellow at the Computer Science Department in the University of Texas as Austin. She received her Ph.D. on plan recognition in real world environments at the Department of Software and Information Systems Engineering in Ben Gurion University. She is interested in the similarities and the differences between AI and natural intelligence, and how these can be used to extend AI. In her research, she seeks algorithms, behaviors and frameworks that can improve existing AI with human-inspired design. In her research, Reuth introduces fundamental theoretical concepts and algorithms by applying them to real problems, putting new spins on them in ways inspired by human intelligence under realistic constraints. Her work has granted her several awards including two awards from the Israeli Ministry of Science (Award for Leading Applied Research and scholarship for Excelling Women in STEM) and the Eric and Wendy Schmidt Postdoctoral Award for Women in Mathematical and Computing Sciences.
https://sites.google.com/site/dekelreuth/