DIFFERENTIAL MODEL OF KALMAN FILTER FOR LOCALIZATION OF AUTONOMOUS MOBILE ROBOTS
With the purpose increase of exactness determination current position autonomous mobile robots is suggested to apply an optimum linear filter for the estimate parameters of odometric sensors. Because of the necessity decline of calculable complication of procedure Kalman Filtration without the decline of exactness, the model Kalman filter is developed on the basis of mathematical vehicle of differential transformations by G.E.Pukhova. The got model allows to take the decision of difficult nonlinear matrix equalization Rikatti at the calculation of covariance matrix errors of filtration to the system of nonlinear algebraic equalizations. For the decision of the system nonlinear algebraic equalizations a method is offered on the basis of approximation subarea method. The results of decision of test task showed high exactness of calculation of matrix coefficient gain of Kalman filter, high accuracy of filtration and transient process.