  As emotion plays a growing role in robotic research it is crucial to develop
methods to analyze and compare among the wide range of approaches. To this end
we present a survey of 1427 IEEE and ACM publications that include robotics and
emotion. This includes broad categorizations of trends in emotion input
analysis, robot emotional expression, studies of emotional interaction and
models for internal processing. We then focus on 232 papers that present
internal processing of emotion, such as using a human's emotion for better
interaction or turning environmental stimuli into an emotional drive for
robotic path planning. We conducted constant comparison analysis of the 232
papers and arrived at three broad categorization metrics; emotional
intelligence, emotional model and implementation, each including two or three
subcategories. The subcategories address the algorithm used, emotional mapping,
history, the emotional model, emotional categories, the role of emotion, the
purpose of emotion and the platform. Our results show a diverse field of study,
largely divided by the role of emotion in the system, either for improved
interaction, or improved robotic performance. We also present multiple future
opportunities for research and describe intrinsic challenges common in all
publications.
