  In this paper we develop a Model Predictive Path Integral (MPPI) control
algorithm based on a generalized importance sampling scheme and perform
parallel optimization via sampling using a Graphics Processing Unit (GPU). The
proposed generalized importance sampling scheme allows for changes in the drift
and diffusion terms of stochastic diffusion processes and plays a significant
role in the performance of the model predictive control algorithm. We compare
the proposed algorithm in simulation with a model predictive control version of
differential dynamic programming.
