Stochastic modelling and identification of industrial robots

Martin Ron, Pavel Burget

Abstract: This paper focuses on identifying the operations of industrial manipulators that are often realised as robots with six degrees of freedom. The identification is based on the measurement of the power consumption of the whole robot without separating it to the individual axes. Such a case corresponds to industrial use cases. The robot is taken as an unobservable system with respect to its internal states. This disadvantage is overcome using hidden time-varying Markov chains. The results are verified on a simple one-axis manipulator and further discussion about the extension of the model is provided.