This paper adopts a Hidden Markov Model as a basis for predicting the probabilities in location of soccer robot’s trajectories, develops the corresponding algorithms, and then demonstrates the simplicity of the procedure with simulations. The purpose of the initial presentation is to establish a proper platform for the future comprehensive studies of using Hidden Markov Models to assemble critical observations with uncertainties or random measurement errors in stochastic system modelling and control.
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