Abstract
Because the internal structure, degree of freedom, skin control position and range of the android face are different, it is very difficult to generate facial expressions by applying existing facial expression generation methods. In addition, facial expressions differ among robots because they are designed subjectively. To address these problems, we developed a system that can automatically generate robot facial expressions by combining an android, a recognizer capable of classifying facial expressions and a genetic algorithm. We have developed two types (older men and young women) of android face robots that can simulate human skin movements. We selected 16 control positions to generate the facial expressions of these robots. The expressions were generated by combining the displacements of 16 motors. A chromosome comprising 16 genes (motor displacements) was generated by applying real-coded genetic algorithms; subsequently, it was used to generate robot facial expressions. To determine the fitness of the generated facial expressions, expression intensity was evaluated through a facial expression recognizer. The proposed system was used to generate six facial expressions (angry, disgust, fear, happy, sad, surprised); the results confirmed that they were more appropriate than manually generated facial expressions.
Highlights
A social robot can deliver information required for everyday life to humans and can interact with humans via two-way communication
The fitness of facial expressions generated with genes was evaluated using FaceReader, a facial expression recognizer software package developed by Noldus in the Netherlands
The two-point exchange method was used for crossover and the Gaussian method was used for mutation
Summary
A social robot can deliver information required for everyday life to humans and can interact with humans via two-way communication. A hotel in Japan introduced an android to confirm the reservation information of clients and guide them to their rooms [4,5]. This system combines interactive technology that responds to clients, vision/recognition technology that can recognize an approaching person and memorize their appearance, voice recognition and dialog technology that can understand what people say and have a conversation and robot control technology that can inform people of their room location via hand gestures. The appearance of social robots takes various forms, depending on their roles and purposes.
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