@misc{Burns23-HRIWS-Lasting,
  title = {A Lasting Impact: Using Second-Order Dynamics to Customize the Continuous Emotional Expression of a Social Robot},
  abstract = {Robots are increasingly being developed as assistants for household, education, therapy, and care settings. Such robots need social skills to interact warmly and effectively with their users, as well as adaptive behavior to maintain user interest. While complex emotion models exist for chat bots and virtual agents, autonomous physical robots often lack a dynamic internal affective state, instead displaying brief, fixed emotion routines to promote or discourage specific user actions. We address this need by creating a mathematical emotion model that can easily be implemented in a social robot to enable it to react intelligently to external stimuli. The robot's affective state is modeled as a second-order dynamic system analogous to a mass connected to ground by a parallel spring and damper. The present position of this imaginary mass shows the robot's valence, which we visualize as the height of its displayed smile (positive) or frown (negative). Associating positive and negative stimuli with appropriately oriented and sized force pulses applied to the mass enables the robot to respond to social touch and other inputs with a valence that evolves over a longer timescale, capturing essential features of approach-avoidance theory. By adjusting the parameters of this emotion model, one can modify three main aspects of the robot's personality, which we term disposition, stoicism, and calmness.},
  howpublished = {Workshop paper (5 pages) presented at the HRI Workshop on Lifelong Learning and Personalization in Long-Term Human-Robot Interaction (LEAP-HRI)},
  address = {Stockholm, Sweden},
  month = mar,
  year = {2023},
  slug = {burns23-hriws-lasting},
  author = {Burns, Rachael Bevill and Kuchenbecker, Katherine J.},
  url = {https://leap-hri.github.io/2023/papers/LEAP-HRI_2023_paper_6433.pdf},
  month_numeric = {3}
}