Modelling and realization of the peg-in-hole task based on hidden Markov model

Impedance control is widely used in the field of industrial world. In a certain task, it is important to decide the impedance parameters in order to realize the desired task. However, it is very difficult to calculate analytically, and the method to extract impedance parameters from human demonstration often exist unevenness in time and space in the human data. Modelling with hidden Markov model (HMM) is known as one of the promising technique to construct an efficient model for time-variant data including unevenness. HMM is capable of characterizing a doubly stochastic process with an underlying immeasurable stochastic process which can be measured through another set of stochastic processes. In this paper, we propose a method to model the series of impedance parameters identified from human teaching data with HMM as human skill model of the peg-in-hole task. In addition, realization method of the task based on the obtained model is shown