collaborators

6 papers

cs.RO2026

Robust Adaptive Predictive Control for Hook-Based Aerial Transportation Between Moving Platforms

Péter Antal, Andrea Carron, Melanie Zeilinger +2

This paper presents a novel model predictive control (MPC) approach for autonomous pick-and-place between moving platforms with a hook-equipped aerial manipulator. First, for accur…

eess.SY2026

Bridging RL and MPC for mixed-integer optimal control with application to Formula 1 race strategies

Joschua Wüthrich, Romir Damle, Giona Fieni +3

We propose a hybrid reinforcement learning (RL) and model predictive control (MPC) framework for mixed-integer optimal control, where discrete variables enter the cost and dynamics…

eess.SY2026

Distributed Predictive Control Barrier Functions: Towards Scalable Safety Certification in Modular Multi-Agent Systems

Jonas Ohnemus, Alexandre Didier, Ahmed Aboudonia +2

We consider safety-critical multi-agent systems with distributed control architectures and potentially varying network topologies. While learning-based distributed control enables…

eess.SY2026

Real-Time Online Learning for Model Predictive Control using a Spatio-Temporal Gaussian Process Approximation

Lars Bartels, Amon Lahr, Andrea Carron +1

Learning-based model predictive control (MPC) can enhance control performance by correcting for model inaccuracies, enabling more precise state trajectory predictions than traditio…

cs.RO2025

An MPC framework for efficient navigation of mobile robots in cluttered environments

Johannes Köhler, Daniel Zhang, Raffaele Soloperto +2

We present a model predictive control (MPC) framework for efficient navigation of mobile robots in cluttered environments. The proposed approach integrates a finite-segment shortes…

cs.RO2025

Constraint-Aware Diffusion Guidance for Robotics: Real-Time Obstacle Avoidance for Autonomous Racing

Hao Ma, Sabrina Bodmer, Andrea Carron +2

Diffusion models hold great potential in robotics due to their ability to capture complex, high-dimensional data distributions. However, their lack of constraint-awareness limits t…