A learned policy rollout is refined by one Newton step via Riccati recursion, yielding quadratic reduction in suboptimality for nonlinear MPC, shown on quadcopter trajectory tracking.
Safe-control-gym: A unified benchmark suite for safe learning-based control and reinforcement learning in robotics,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Rollout Then Optimize: A One-Step Newton Refinement of Learned Policies for Nonlinear Model Predictive Control
A learned policy rollout is refined by one Newton step via Riccati recursion, yielding quadratic reduction in suboptimality for nonlinear MPC, shown on quadcopter trajectory tracking.