Application of Risk Sensitive Optimal Filtering Equations to a Wheeled Mobile Robot on an Inclined Plane

In this work the Risk-Sensitive (RS) optimal filtering equations for polynomial stochastic systems of first degree were applied for modelling the dynamical system of a wheeled mobile robot in an inclined plane with linear observations and with stochastic term. The parameter epsilon is a diffusion coefficient, and can take some values that in-crease the noise into the state and the observations equations. The performance of these RS filters was compared vs polynomial filtering equations. Simulation results show that the error values are smaller for RS filtering equations for all values of the diffusion parameter epsilon in final time T.