activity
20242026
most citedCooperative distributed model predictive control for embedded systems: Experiments with hovercraft formations

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

math.OC2026

GPU-Accelerated Cholesky Factorization of Block Tridiagonal Matrices

Roland Schwan, Daniel Kuhn, Colin N. Jones

This paper presents a GPU-accelerated framework for solving block tridiagonal linear systems that arise naturally in numerous real-time applications across engineering and scientif…

math.OC2025

Parallel KKT Solver in PIQP for Multistage Optimization

Fenglong Song, Roland Schwan, Yuwen Chen +1

This paper presents an efficient parallel Cholesky factorization and triangular solve algorithm for the Karush-Kuhn-Tucker (KKT) systems arising in multistage optimization problems…

math.OC2025

Exploiting Multistage Optimization Structure in Proximal Solvers

Roland Schwan, Daniel Kuhn, Colin N. Jones

This paper presents an efficient structure-exploiting algorithm for multistage optimization problems. The proposed method extends existing approaches by supporting full coupling be…

cs.RO2024★ 1 cited

Cooperative distributed model predictive control for embedded systems: Experiments with hovercraft formations

Gösta Stomberg, Roland Schwan, Andrea Grillo +2

This paper presents experiments for embedded cooperative distributed model predictive control applied to a team of hovercraft floating on an air hockey table. The hovercraft collec…

eess.SY2024

On identifying the non-linear dynamics of a hovercraft using an end-to-end deep learning approach

Roland Schwan, Nicolaj Schmid, Etienne Chassaing +2

We present the identification of the non-linear dynamics of a novel hovercraft design, employing end-to-end deep learning techniques. Our experimental setup consists of a hovercraf…