Clustering of Humanoid Robot Motions Executed in Response to Touch

Abstract

We perform a study on responses that should be performed by robots when touched by humans. To study the kinds of robot responses in general, there is a need for clustering similar responses. We present the use of Multiple correspondence analysis (MCA) and hierarchical clustering method as a way of clustering different humanoid robot postures. MCA is commonly used to analyze data with discrete variables. Since clustering solely by MCA was impractical for our application, hierarchical clustering method was performed to aid the direct inspection of the robot response clusters.