RL-Guided PAC-NMPC for Probabilistically-Safe Perception-Based Navigation in Unknown Environments

In this paper, we present an approach for combining stochastic nonlinear model predictive control (SNMPC) and reinforcement learning (RL) to enable probabilistically-safe perception-based navigation in unknown environments. Our method first uses RL to train probabilistic actor-critic and sensor prediction models.

From the abstract. Our summary is in progress.