Suguitan M. & Hoffman G. (2018).
Affective Robot Movement Generation Using CycleGANs

Companion of the 2019 ACM/IEEE International Conference on Human-Robot Interaction (HRI) : 534-535

3rd Place (LBR)
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Abstract

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).