My research has been focused on human-robot interaction, especially on modeling human behavior, simulating natural and effective social behaviors for robots, and investigating how robots might leverage social behaviors to interact with their users to achieve desired interaction outcomes.
Robot Behavior Toolkit | HRI'12 | Paper
achieve fluent and effective humanlike communication, robots must
seamlessly integrate the necessary social behaviors for a given interaction context.
We propose a framework that guides the generation of social behavior
for humanlike robots by systematically using specifications of
social behavior from the social sciences and contextualizing these
specifications in an Activity-Theory-based interaction model. The Robot Behavior Toolkit is an open-source implementation
of this framework as a Robot Operating System (ROS) module.
Joint attention in HRI | RoMan'11 | Paper
Joint attention is a crucial component in interaction. Inspired by the developmental timeline of
joint attention in humans, we proposed a conceptual model of joint attention with three parts:
responding to joint attention, initiating joint attention, and ensuring joint attention.
We found that (1) a robot responding to joint attention improves task performance and is perceived as more competent and socially interactive,
and that (2) a robot's ensuring joint attention behavior is judged as having better performance in
human-robot interactive tasks and is perceived as a natural behavior.