center for robotics and embedded systems University of Southern California Viterbi School of Engineering


In this paper, we present a metric for assessing the quality of arm movement imitation. We develop a joint-rotational-angle-based segmentation and comparison algorithm that rates pairwise similarity of arm movement trajectories on a scale of 1-10. We describe an empirical study designed to validate the algorithm we developed, by comparing it to human evaluation of imitation. The results provide evidence that the evaluation of the automated metric did not significantly differ from human evaluation.


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