With the ultimate goal of producing natural-looking movements in humanoid robots and virtual humans, we examined the visual perception of movements generated by different models of movement generation. The models of movement generation included 14 synthetic motion generation algorithms based on theories of human motor production. In addition, we obtained motion from recordings of actual human movement. The resulting movements were applied to both a humanoid robot and a computer graphics virtual human. The computational efficiency of the motion production algorithms is described. In Experiment 1, we examined observers' judgments of the naturalness of a movement. Results showed that, for the humanoid robot, low ratings of naturalness were obtained for rapid movement. In addition, it was found that some movements that appeared to have unremarkable naturalness ratings were anomalous examples of the desired movement. In Experiment 2, we used naturalness ratings to study the influence of movement speed on the humanoid robot. Results indicated that the decrease in naturalness was due to motion artifacts at the ends of the movement. In Experiment 3, we returned to the issue of anomalous movements by obtaining ratings of similarity between pairs of movements, and analyzing these with multi-dimensional scaling to obtain a psychological space representation of the set of movements. Results showed that the presumed anomalous movements were indeed distinctive from the other movements, suggesting that the naturalness judgments did not completely indicate the perception of movement. We discuss these results in the context of what they suggest for the relative effectiveness of the different generation algorithms at producing natural movement, and their relative computational efficiency, as well as in terms of the effectiveness of different psychological techniques for the assessment of humanoid movement.
Lip Motion Generation Method Based on Formants for Tele-presence Humanoid Robots
