Consideration about the Application of Dynamic Time Warping to Human Hands Behavior Recognition for Human-Robot Interaction

To prepare the age when humans and robots live together, robots need to understand the meaning of human behaviors for the natural and rational human-robot interaction (HRI). The robot particularly needs to recognize the human hands behavior, since humans usually express their meanings and intentions by using two hands. In this paper, the robot recognizes the human hands behavior by simulating it based on robot’s own hands behaviors set and finding the most similar one as human behavior using dynamic time warping (DTW) algorithm. To consider the effects of different variables, i.e. data normalization methods and local cost measures for DTW algorithm, this paper considers two different normalization methods and four different local cost measures and their effects are discussed. The robot successfully recognizes the eight different human hands behaviors by DTW algorithm with the chosen normalization methods and local cost measures.