Conditional generative adversarial network for generating communicative robot gestures
2020 29th IEEE International Conference on Robot and Human …, 2020•ieeexplore.ieee.org
Non-verbal behaviors have an indispensable role for social robots, which help them to
interact with humans in a facile and transparent way. Especially, communicative gestures
allow robots to have the capability of using bodily expressions for emphasizing the meaning
of their speech, describing something, or showing clear intention. This paper presents an
approach to learn the synthesis of human actions and natural language. The generative
framework is inspired by Conditional Generative Adversarial Network (CGAN), and it makes …
interact with humans in a facile and transparent way. Especially, communicative gestures
allow robots to have the capability of using bodily expressions for emphasizing the meaning
of their speech, describing something, or showing clear intention. This paper presents an
approach to learn the synthesis of human actions and natural language. The generative
framework is inspired by Conditional Generative Adversarial Network (CGAN), and it makes …
Non-verbal behaviors have an indispensable role for social robots, which help them to interact with humans in a facile and transparent way. Especially, communicative gestures allow robots to have the capability of using bodily expressions for emphasizing the meaning of their speech, describing something, or showing clear intention. This paper presents an approach to learn the synthesis of human actions and natural language. The generative framework is inspired by Conditional Generative Adversarial Network (CGAN), and it makes use of the Convolutional Neural Network (CNN) with the Action Encoder/Decoder for action representation. The experimental and comparative results verified the efficiency of the proposed approach to produce human actions synthesized with text descriptions. Finally, through the Transformation model, the generated data were converted to a set of joint angles of the target robot, being the robot’s communicative gestures. By employing the generated human-like actions for robots, it suggests that robots’ social cues could be more understandable by humans.
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