Date: 10/27/2022
Speaker: Xiang Zhi Tan
Location: 122 Gates Hall and Zoom
Time: 2:40 p.m.-3:30 p.m.
Abstract: As more robots are deployed in the world, human-robot interaction will not be limited to one-to-one interactions between users and robots. Instead, users will likely have to interact with multiple robots and other embodied intelligences, simultaneously or sequentially, throughout their day to receive services and complete different tasks. In this talk, I will describe work, in collaboration with my colleagues, that broadens the knowledge on a crucial aspect of multi-robot human interaction: person transfer, or the act of transferring users between multiple service robots. We first investigated rationales for transfer and important aspects of transferring users. We then explored how person transfers should be designed and implemented in laboratory and field settings. We used a combination of design, behavioral, and technical methods to increase our understanding of this crucial phase and inform developers and designers about appropriate robot behaviors when a human is being transferred from one robot to another.
Bio: Xiang Zhi Tan, PhD, is a postdoctoral fellow working with Prof. Sonia Chernova in the Robot Autonomy and Interactive Learning (RAIL) Lab at Georgia Institute of Technology. His research focuses on designing algorithms and deploying robotic systems to facilitate a better understanding of how multiple robots can seamlessly interact with people. He received his PhD in Robotics in 2021 from Carnegie Mellon University’s Robotics Institute, where he was advised by Prof. Aaron Steinfeld. He holds a Bachelor of Science degree from University of Wisconsin-Madison and a Master of Science degree from Carnegie Mellon University. Outside of research, he has been trying to figure out how to be ambidextrous.
Website: zhi.fyi