Repository: https://github.com/LemonPi/pytorch_mppi

I made a pytorch implementation of the algorithm from Information theoretic MPC for model-based reinforcement learning that should be a better drop-in for MPC if you’re using random shooting or the cross entropy method (CEM)

Some features – batch sampling of trajectories (optionally on the GPU) – general to problem dimension – only requires approximate dynamics, which can be implemented as a network (MPPI originally requires sampling from the true dynamics, but this formulation uses importance sampling)