Abstract
When human interacts with robots or machines, many skills such as cognition, planning, and control are
involved. However, it is difficult to perform in every single one of these fields. Therefore, assist regarding
human-machine operation has been actively researched. For instance, a method used to feedback surrounding
information using a camera is used in automobiles. However, it has been reported that this method reduces
human concentration. In order to solve this problem, assist methods using tactile feedback and force feedback
has been proposed and demonstrated their usefulness as a way for humans to obtain feedback more naturally.
Among them, we focused on subliminal calibration. Subliminal calibration is an algorithm that focuses on the
process of acquiring skills and determines the value of the calibration so that the process doesn’t disturb the
operator. The purpose of this research to enhance the operator’s skills in order to help him operate machines at will. In this paper, we investigated the change of the personal model in response to the dynamics change. As a result, it was confirmed that the personal model followed the dynamics by subliminal calibration. In addition, it was suggested that the performance could be improved by using the aforementioned results.
