Functional mode estimation using principal component analysis of grasping/manipulating motion

Recently, significant developments have been made in motion control technology. Robots are used not only in industry but also in everyday human society. Hereafter, in order to extend the range of the work and the types of motion, it is necessary to think about what being human means. Human beings are able to do a variety of work using the fingers, arms, and eyes. The motion trajectory and force adjustment are different in each of motion. Hence, which component is dominant for a particular work must be identified. In the conventional method for the quantitative analysis of human motion, it is presupposed that the functional mode is predefined, such as the grasping mode and the manipulating mode. In this paper, an estimation method using the principal component analysis (PCA) of the functional mode for human motion is proposed. Using this method, the dominant function is directly estimated from the motion information. The validity of the proposal is confirmed by three types of experiments. To confirm their effectiveness, these experiments are conducted under a condition whose theoretical value is known to exist. The experimental results in this paper are compared with the theoretical value, and a good agreement is observed.