Robot Behavior Toolkit | HRI'12 | Paper
To 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.