activity
20162026
most citedEmbedded nonlinear model predictive control for obstacle avoidance using PANOC

100 citations · 251 across the 76 of their papers we have counts for

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Showing 2021Show all

12 papers · 1 filter

math.OC2021★ 1 cited

Alpaqa: A matrix-free solver for nonlinear MPC and large-scale nonconvex optimization

Pieter Pas, Mathijs Schuurmans, Panagiotis Patrinos

This paper presents alpaqa, an open-source C++ implementation of an augmented Lagrangian method for nonconvex constrained numerical optimization, using the first-order PANOC algori…

math.OC2021★ 2 cited

Dualities for non-Euclidean smoothness and strong convexity under the light of generalized conjugacy

Emanuel Laude, Andreas Themelis, Panagiotis Patrinos

Relative smoothness and strong convexity have recently gained considerable attention in optimization. These notions are generalizations of the classical Euclidean notions of smooth…

math.OC2021★ 20 cited

Learning MPC for Interaction-Aware Autonomous Driving: A Game-Theoretic Approach

Brecht Evens, Mathijs Schuurmans, Panagiotis Patrinos

We consider the problem of interaction-aware motion planning for automated vehicles in general traffic situations. We model the interaction between the controlled vehicle and surro…

math.OC2021★ 13 cited

Block Alternating Bregman Majorization Minimization with Extrapolation

Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis +2

In this paper, we consider a class of nonsmooth nonconvex optimization problems whose objective is the sum of a block relative smooth function and a proper and lower semicontinuous…

math.OC2021★ 1 cited

Massively parallelizable proximal algorithms for large-scale stochastic optimal control problems

Ajay K. Sampathirao, Panagiotis Patrinos, Alberto Bemporad +1

Scenario-based stochastic optimal control problems suffer from the curse of dimensionality as they can easily grow to six and seven figure sizes. First-order methods are suitable a…

math.OC2021★ 3 cited

A General Framework for Learning-Based Distributionally Robust MPC of Markov Jump Systems

Mathijs Schuurmans, Panagiotis Patrinos

We present a learning model predictive control (MPC) scheme for chance-constrained Markov jump systems with unknown switching probabilities. Using samples of the underlying Markov…