Toward Single-Step MPPI via Differentiable Predictive Control
Step-MPPI is a framework that learns a neural network to parameterize sampling distributions for Model Predictive Path Integral (MPPI) control. This allows for efficient single-step lookahead MPPI updates while maintaining the foresight of a long-horizon optimizer, achieving millisecond latency and better robustness than standard methods.