Dance-like humanoid motion generation through foot touch states classification

This paper proposes a humanoid dance motion generation system that deals with a huge variety of leg motions. While previous research only tackled on a few kinds of leg motions, original human dance leg motions contain various foot touch states such as slide, turn, and heel contact, as well as complex motions such as kick and twist. According to the dance literature, we found that there are seven major foot touch states that make dance motion more “dance-like”. Thus we present a method to classify the seven kinds of foot touch state from human dance motion data, and describe the various dance leg motions by using combinations of the foot touch states and key-frames. Based on these methods, we designed the humanoid dance motion generation system that enables humanoid robots not only to satisfy the geometric condition but also to imitate various human dance leg motions. Finally we show an experiment using a life-sized humanoid, HRP-2.