Robotics, Kalman Filter, Robot Operating System, State Estimation, Artificial Intelligence.
predicted μ^bar_t using the action model. This process involves evolving the state forward in time through the matrix A and then incorporating the effect of the controls by adding the product of the controls and the matrix B. As for the noise ϵ_t​, it is Gaussian, with mean μ=0 and covariance Σ=R,