The relationship between man and machine has long been the focus of studies and research from different scientific areas. Since the Industrial Revolution, man finds himself having to interact and collaborate with machines and wonders, in this sense, on the best way to communicate with them. The mechanical machine has always been considered the machine par excellence, a man substitute in performing physical activities. In fact, initially man was involved in mechanical applications to produce goods, this was followed by, in addition to the previous functions, the transmission of information and therefore the definition of a new form of communication. This is how a qualitative evolution of the functions of machines is configured: the concept of feedback emerges which implies a reaction of the machine to an action generated by man (Bonsiepe, 1963). With the use of advanced technologies and new robot features, this relationship has become complicated, up to the point where, in some cases, the hierarchy between man and machine has become very unstable. Today, the potential of robots makes it possible to use new communication channels to improve interaction with them and make it more intuitive and natural. In fact, the multimodal information provided by both the robot and the user ensures reduced communication times and is very effective as the presence of variable noise and lighting conditions can lead to a reduction in the communication channel and invalidate the interaction itself. An effective interaction, in fact, involves the user through his posture, face and gesture. In literature, there are different coding systems of facial expressions such as Ekman’s FACS or the classification of facial expressions by El Kaliouby and Robinson: the first one is organized on the identification of the movements of the face and head; the second one is based on the combination of sequences identified through a dynamic Bayesian network as regards facial expression. The latter system detects the user’s moods that are fundamental in ...


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    Titel :

    Human-robot interaction. Face stereotypes in anthropomorphic robotic systems



    Erscheinungsdatum :

    01.01.2022


    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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