20 citations · 49 across the 19 of their papers we have counts for
5 papers · 1 filter
Safe, Learning-Based MPC for Highway Driving under Lane-Change Uncertainty: A Distributionally Robust Approach
Mathijs Schuurmans, Alexander Katriniok, Christopher Meissen +2
We present a case study applying learning-based distributionally robust model predictive control to highway motion planning under stochastic uncertainty of the lane change behavior…
Learning-Based Risk-Averse Model Predictive Control for Adaptive Cruise Control with Stochastic Driver Models
Mathijs Schuurmans, Alexander Katriniok, Hongtei Eric Tseng +1
We propose a learning-based, distributionally robust model predictive control approach towards the design of adaptive cruise control (ACC) systems. We model the preceding vehicle a…
Data-driven distributionally robust LQR with multiplicative noise
Peter Coppens, Mathijs Schuurmans, Panagiotis Patrinos
We present a data-driven method for solving the linear quadratic regulator problem for systems with multiplicative disturbances, the distribution of which is only known through sam…
Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC
Alexander Katriniok, Pantelis Sopasakis, Mathijs Schuurmans +1
The coordination of highly automated vehicles (or agents) in road intersections is an inherently nonconvex and challenging problem. In this paper, we propose a distributed motion p…
Safe Learning-Based Control of Stochastic Jump Linear Systems: a Distributionally Robust Approach
Mathijs Schuurmans, Pantelis Sopasakis, Panagiotis Patrinos
We consider the problem of designing control laws for stochastic jump linear systems where the disturbances are drawn randomly from a finite sample space according to an unknown di…