A study of extraction method of motion patterns observed frequently from time-series posture data

In this paper, we describe a motion pattern acquisition system from time-series posture data for a robot. In order to extract reusable motion patterns without the target pattern information a priori, proposed system extracts the patterns observed frequently. The extracted motion patterns often include transition motion at first and last. In order to reduce the transition part, we propose common block extraction method. The similar common block is classified to the same category. Then, the proposed system obtains the average of each cluster as representative motion patterns. Experimental results show remarkable motion patterns extracted by proposed system from time-series posture data.