Title: Improving Human-Robot Conversational Groups

Abstract: This work aims to improve human-robot conversational groups, in which a robot is situated in an F-formation with humans. With a naive look, each robot consists of input devices e.g., sensors, cameras, etc. logic and decision-making blocks e.g., face detection algorithm, NLP, etc., and output devices e.g., actuators and speakers, etc. These components connect serially. Each component is prone to errors; therefore, each error feeds into the next component and decreases the overall efficiency of the system. For example, if the camera cannot see a person because of being obstructed by an object, then the human detection algorithm cannot detect that person and then the robot won't consider that person in the interaction. These types of errors decrease the efficiency of the system and also negatively impact human-robot interaction. In this work, we propose four systems that aim to help understand human-robot conversational groups better, reason about them, find the mentioned errors and overcome them. First, we look at the difference between human-human conversational groups and human-robot conversation groups. Second, we propose an algorithm to detect conversational groups (F-formations). Third, we look at how to detect missing people in the conversational groups and validate human-detection algorithms. Last, we propose an algorithm to detect the active speaker based on visual cues and help robots behave normally in conversational groups.

Speaker Bio: Hooman Hedayati works in human-robot interaction, machine learning, and robotics, seeking more seamless, safer, and intuitive ways for people to interact with computationally controlled devices. Hooman is a CU Boulder alumnus and his advisor was Dr. Dan Szafir. Currently, he is a post-doc researcher at the University of North Carolina Chapel Hill. He worked at high prestigious research labs such as Microsoft Research and Disney Research. His work includes studying the interactions between flying robots and humans, developing algorithms to support more socially sensitive behavior for robots, and using augmented reality to make working with robots more productive and safer.


Zoom bilgileri:

Topic: ROMER Seminar Series

Time: Feb 17, 2022 01:30 PM Istanbul

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Meeting ID: 937 2526 0959

Passcode: 702838

Last Updated:
16/02/2022 - 10:39