Abstract
This paper integrated Gross cognitive process into the HMM (hidden Markov model) emotional regulation method and implemented human-robot emotional interaction with facial expressions and behaviors. Here, energy was the psychological driving force of emotional transition in the cognitive emotional model. The input facial expression was translated into external energy by expression-emotion mapping. Robot’s next emotional state was determined by the cognitive energy (the stimulus after cognition) and its own current emotional energy’s size and source’s position. The two random quantities in emotional transition process—the emotional family and the specific emotional state in the AVS (arousal-valence-stance) 3D space—were used to simulate human emotion selection. The model had been verified by an emotional robot with 10 degrees of freedom and more than 100 kinds of facial expressions. Experimental results show that the emotional regulation model does not simply provide the typical classification and jump in terms of a set of emotional labels but that it operates in a 3D emotional space enabling a wide range of intermediary emotional states to be obtained. So the robot with cognitive emotional regulation model is more intelligent and real; moreover it can give full play to its emotional diversification in the interaction.
Highlights
Nowadays, robot needs intelligent behavior and needs mental life, such as cognition, emotion, and personality
The noteworthy feature of emotional regulation work was out of the interactive mode providing the classification and jump in terms of a set of emotional labels, and it operated in a 3D emotional space enabling a wide range of intermediary emotional states obtained under the external stimulus
This system focused on the research field of emotional regulation depending on natural facial expression cognition and proposed a microexpression cognition and emotional regulation model based on Gross reappraisal strategy
Summary
Robot needs intelligent behavior and needs mental life, such as cognition, emotion, and personality. Several valued and far-reaching approaches about emotion modeling have been proposed They can be divided into two categories: the discrete model and the emotional space model. Ortony et al model the OCC reasoning process that can produce the cognitive emotions and touch off complex emotional experiences via the trend of events (including event, object, and agent) [18]. This model has been developed and refined by Yang et al and Kim et al [21, 22]. This paper discussed a cognitive emotional regulation model in the active field state space.
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