11 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
AC4MPC: Actor-Critic Reinforcement Learning for Nonlinear Model Predictive Control
Rudolf Reiter, Andrea Ghezzi, Katrin Baumgärtner +3
\Ac{MPC} and \ac{RL} are two powerful control strategies with, arguably, complementary advantages. In this work, we show how actor-critic \ac{RL} techniques can be leveraged to imp…
Equivariant Deep Learning of Mixed-Integer Optimal Control Solutions for Vehicle Decision Making and Motion Planning
Rudolf Reiter, Rien Quirynen, Moritz Diehl +1
Mixed-integer quadratic programs (MIQPs) are a versatile way of formulating vehicle decision making and motion planning problems, where the prediction model is a hybrid dynamical s…
A Long-Short-Term Mixed-Integer Formulation for Highway Lane Change Planning
Rudolf Reiter, Armin Nurkanovic, Daniele Bernadini +2
This work considers the problem of optimal lane changing in a structured multi-agent road environment. A novel motion planning algorithm that can capture long-horizon dependencies…
Progressive Smoothing for Motion Planning in Real-Time NMPC
Rudolf Reiter, Katrin Baumgärtner, Rien Quirynen +1
Nonlinear model predictive control (NMPC) is a popular strategy for solving motion planning problems, including obstacle avoidance constraints, in autonomous driving applications.…