Model of human actions by a Petri net and prediction of human acts (for generation of home robots movement based on prediction of human actions)

A home robot (a robot used in the home) must recognize the intention of a person in the home, in order to support that person. It is important to construct intelligence with which a robot can predict the person's next act and help him or her if required. In this paper, a robust system which predicts vague human actions is proposed. Human actions can be modeled by a stochastic process in digital time and discrete states: this stochastic process is visualized using a Petri net. A series of human actions is a chain of states and acts. A human state is expressed as a place, and a human act as a transition. A stochastic act is described as a predicting transition, and transition probability to plural states is given. If the system makes a wrong prediction, the transition probability is renewed. As time progresses, the level of this intelligence increases, and the prediction will be accurate with high probability.