Human-like facial expression imitation for humanoid robot based on recurrent neural network

To generate natural and less hardwired facial expression for humanoid robots, a facial motion imitation method, which transfers facial geometric characteristics of humans to robots, is proposed. Firstly, for mapping servo control space into facial expression space, a forward kinematics model with sequence is built based on recurrent neural network. Secondly, the process of expression imitation for humanoid robot is converted to an optimization with the proposed forward kinematics model and servo sequential constraints. Finally, we conduct some experiments on the rationality of proposed model as well as the validity of optimization strategy. Compared with the art-of-the-state of methods, the proposed method not only has smaller expression deviations with the performer, but also keeps smooth servo movements in dynamic facial imitation.