Robotics

Probabilistic state estimation for robotics applications. Bayes filters include Kalman, Markov chains; Gaussian, uniform and discrete mapping probability distributions representations; Distribution sampling, marginalization, multiplication; Distribution composition independent pairs and Bayes rule; Linear algebra, matrix, vector, inverse, square root, LU decomposition, Cholesky decomposition; piecewise linear approximation of functions; Sensor models, Markov action chains <X,U,X>.