11 papers
Learning Dynamic Games for Cooperative Iterative Tasks
Mark Pustilnik, Francesco Borrelli
We consider cooperative and iterative tasks involving multiple agents whose interactions are modeled as a dynamic game with shared constraints. We propose a general learning framew…
Data-Driven Modeling and Predictive Control of Chronic Diseases: An Ulcerative Colitis Application
Fionna B. Kopp, Ann-Kathrin Schalkamp, Shadera Azzam +2
The clinical management of chronic disease is naturally structured as a feedback control problem. Physicians observe the disease state at clinic visits and make decisions based on…
Non Normalized Shared-Constraint Dynamic Games for Human-Robot Collaboration with Asymmetric Responsibility
Mark Pustilnik, Francesco Borrelli
This paper proposes a dynamic game formulation for cooperative human-robot navigation in shared workspaces with obstacles, where the human and robot jointly satisfy shared safety c…
Non-Normalized Solutions of Generalized Nash Equilibrium in Autonomous Racing
Mark Pustilnik, Antonio Loquercio, Francesco Borrelli
In dynamic games with shared constraints, Generalized Nash Equilibria (GNE) are often computed using the normalized solution concept, which assumes identical Lagrange multipliers f…
On Sampling Time and Invariance
Spencer Schutz, Charlott Vallon, Ben Recht +1
Invariant sets define regions of the state space where system constraints are always satisfied. The majority of numerical techniques for computing invariant sets have been develope…
Generalized Nash Equilibrium Solutions in Dynamic Games With Shared Constraints
Mark Pustilnik, Francesco Borrelli
In dynamic games with shared constraints, Generalized Nash Equilibria (GNE) are often computed using the normalized solution concept, which assumes identical Lagrange multipliers f…
Data-Driven Multi-Modal Learning Model Predictive Control
Fionna B. Kopp, Francesco Borrelli
We present a Learning Model Predictive Controller (LMPC) for multi-modal systems performing iterative control tasks. Assuming availability of historical data, our goal is to design…
Multi-Objective Learning Model Predictive Control
Siddharth H. Nair, Charlott Vallon, Francesco Borrelli
Multi-Objective Learning Model Predictive Control is a novel data-driven control scheme which improves a linear system's closed-loop performance with respect to several convex cont…
Learning Hierarchical Control For Multi-Agent Capacity-Constrained Systems
Charlott Vallon, Alessandro Pinto, Bartolomeo Stellato +1
This paper introduces a novel data-driven hierarchical control scheme for managing a fleet of nonlinear, capacity-constrained autonomous agents in an iterative environment. We prop…
Clustering Heuristics for Robust Energy Capacitated Vehicle Routing Problem (ECVRP)
Mark Pustilnik, Francesco Borrelli
The paper presents an approach to solving the Robust Energy Capacitated Vehicle Routing Problem (RECVRP), focusing on electric vehicles and their limited battery capacity. A finite…
Learning Hierarchical Control Systems for Autonomous Systems with Energy Constraints
Charlott Vallon, Mark Pustilnik, Alessandro Pinto +1
This paper focuses on the design of hierarchical control architectures for autonomous systems with energy constraints. We focus on systems where energy storage limitations and slow…