利用CycleGANs生成情感机器人运动

Michael Suguitan, Mason Bretan, Guy Hoffman
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引用次数: 10

摘要

社交机器人使用手势来表达内部和情感状态,但它们的互动能力受到依赖于预编程或手动动画行为的阻碍,这些行为可能是重复的和可预测的。我们提出了一种方法来自动合成情感机器人运动给定的人工生成的例子。我们的方法是基于深度学习的技术,特别是生成对抗神经网络(gan)。
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Affective Robot Movement Generation Using CycleGANs
Social robots use gestures to express internal and affective states, but their interactive capabilities are hindered by relying on preprogrammed or hand-animated behaviors, which can be repetitive and predictable. We propose a method for automatically synthesizing affective robot movements given manually-generated examples. Our approach is based on techniques adapted from deep learning, specifically generative adversarial neural networks (GANs).
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