  In this work we evaluate Iterative Linear Quadratic Regulator(ILQR) for
trajectory tracking of two different kinds of wheeled mobile robots namely
Warthog (Fig. 1), an off-road holonomic robot with skid-steering and Polaris
GEM e6 [1], a non-holonomic six seater vehicle (Fig. 2). We use multilayer
neural network to learn the discrete dynamic model of these robots which is
used in ILQR controller to compute the control law. We use model predictive
control (MPC) to deal with model imperfections and perform extensive
experiments to evaluate the performance of the controller on human driven
reference trajectories with vehicle speeds of 3m/s- 4m/s for warthog and
7m/s-10m/s for the Polaris GEM
