PI-MPC turns finite-horizon optimal control into inference over a Boltzmann-weighted control distribution and generates actions via variational inference, with MPPI as a key sampling-based example.
Real-time sampling-based model predictive con- trol based on reverse kullback-leibler divergence and its adaptive acceleration.arXiv preprint arXiv:2212.04298, 2022
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Model Predictive Control via Probabilistic Inference: A Tutorial and Survey
PI-MPC turns finite-horizon optimal control into inference over a Boltzmann-weighted control distribution and generates actions via variational inference, with MPPI as a key sampling-based example.