Affective Human-Humanoid Interaction Through Cognitive Architecture

Abstract

Development of humanoid robots has to address two vital aspects, namely physical appearance and gestures, that will allow the machines to closely resemble humans. Other aspects such as and will enable human-machine interaction to be as natural as possible. The field of robotics has long been investigating how effective interaction between humans and autonomous and intelligent mechanical system can be possible (Goodrich & Schultz., 2007). Several distinctive features have been determined depending on whether a robot that acts as an assistant (for example, in the course of a business) or as a companion is required. In the case of humanoid robots, the human appearance and behavior may be very closely linked and integrated if you adopt a cognitive architecture that can take advantage of the natural mechanisms for exchange of information with a human. The robot that cooperates in the execution of an activity would benefit from the execution of its tasks if it had a mechanism that is capable of recognizing and understanding human activity and intention (Kelley et al., 2010), with perhaps the possibility of developing imitation learning by observation mechanisms. On the other hand, if we consider the robot as a partner, then it plays an important role in sharing the emotional aspects: it is not essential to equip the robot with emotions, but it is important that it can detect human emotional states (Malatesta et al. 2009). The cognitive architectures allow software to deal with problems that require contributions from both the cognitive sciences and robotics, in order to achieve social behavior typical of the human being, which would otherwise be difficult to integrate into traditional systems of artificial intelligence. Several cognitive models of the human mind can find common ground and experimental validation using humanoid agents. For example, if we approach the study of actions and social interactions involving embodied agents, the concept of motor resonance investigated in humans may play an important role (Chaminade & Cheng, 2009) to achieve sophisticated, yet simple to implement, imitative behaviors, learning by demonstration, and understanding of the real scene. In recent years, there is often talk of mirror neurons, which are evidence of the physiological motor resonance at the cellular level with regard to action, action understanding and imitation. But the resonance is applicable in other contexts such as cognitive emotions, the sensations of physical pain, and in various components of the actions of agents interacting socially (Barakova & Lourens, 2009; Fogassi, 2011). Cognitive models proposed would make the humanoid robot capable of overcoming the socalled Uncanny Valley of eeriness (Saygin et al., 2011), by allowing the humanoid is