3 citations · 4 across the 14 of their papers we have counts for
16 papers
Reachability-Guided Sequential Quadratic Programming-Guarded Model Predictive Path Integral for Safe Nonlinear Predictive Control
Alexandre Didier, Jason J. Choi, Namhoon Cho +2
Safe robot control often requires combining long-horizon performance optimization with hard state and input constraints, but existing approaches tend to address this tradeoff parti…
Grounding Generative Policies in Physics: Optimization-Guided Diffusion for Robot Control
Sabrina Bodmer, René Zurbrügg, Tifanny Portela +5
Diffusion models sample effectively from high-dimensional, multimodal distributions, but their outputs may violate deployment constraints. For task-space robot policies, generated…
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…
Eigenvalues as a Metric for Memory Dynamics in Sequence Models
Rahel Rickenbach, Jelena Trisovic, Alexandre Didier +2
While softmax attention drives state-of-the-art performance in sequence modeling, its quadratic complexity motivates linear alternatives such as state space models (SSMs). Structur…
A multiobjective approach to robust predictive control barrier functions for discrete-time systems
Alexandre Didier, Melanie N. Zeilinger
We present an optimisation-based approach to ensure robust asymptotic stability stability of a desired set in the state space of nonlinear dynamical systems, while optimising a gen…
Stochastic MPC with Online-optimized Policies and Closed-loop Guarantees
Marcell Bartos, Alexandre Didier, Jerome Sieber +2
This paper proposes a stochastic model predictive control method for linear systems affected by additive Gaussian disturbances that optimizes over disturbance feedback matrices onl…
Moving Horizon Estimation for Simultaneous Localization and Mapping with Robust Estimation Error Bounds
Jelena Trisovic, Alexandre Didier, Simon Muntwiler +1
This paper presents a robust moving horizon estimation (MHE) approach with provable estimation error bounds for solving the simultaneous localization and mapping (SLAM) problem. We…
Approximate predictive control barrier function for discrete-time systems
Alexandre Didier, Melanie N. Zeilinger
We propose integrating an approximation of a predictive control barrier function (PCBF) in a safety filter framework, resulting in a prediction horizon independent formulation. The…
Computationally Efficient System Level Tube-MPC for Uncertain Systems
Jerome Sieber, Alexandre Didier, Melanie N. Zeilinger
Tube-based model predictive control (MPC) is one of the principal robust control techniques for constrained linear systems affected by additive disturbances. While tube-based metho…
Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
Jerome Sieber, Carmen Amo Alonso, Alexandre Didier +2
Softmax attention is the principle backbone of foundation models for various artificial intelligence applications, yet its quadratic complexity in sequence length can limit its inf…
Predictive stability filters for nonlinear dynamical systems affected by disturbances
Alexandre Didier, Andrea Zanelli, Kim P. Wabersich +1
Predictive safety filters provide a way of projecting potentially unsafe inputs, proposed, e.g. by a human or learning-based controller, onto the set of inputs that guarantee recur…
Approximate Predictive Control Barrier Functions using Neural Networks: A Computationally Cheap and Permissive Safety Filter
Alexandre Didier, Robin C. Jacobs, Jerome Sieber +2
A predictive control barrier function (PCBF) based safety filter is a modular framework to verify safety of a control input by predicting a future trajectory. The approach relies o…
Generalised Regret Optimal Controller Synthesis for Constrained Systems
Alexandre Didier, Melanie N. Zeilinger
This paper presents a synthesis method for the generalised dynamic regret problem, comparing the performance of a strictly causal controller to the optimal non-causal controller un…
A System Level Approach to Regret Optimal Control
Alexandre Didier, Jerome Sieber, Melanie N. Zeilinger
We present an optimisation-based method for synthesising a dynamic regret optimal controller for linear systems with potentially adversarial disturbances and known or adversarial i…
Adaptive Model Predictive Safety Certification for Learning-based Control -- Extended Version
Alexandre Didier, Kim P. Wabersich, Melanie N. Zeilinger
We propose an adaptive Model Predictive Safety Certification (MPSC) scheme for learning-based control of linear systems with bounded disturbances and uncertain parameters where the…
Robust Adaptive Model Predictive Control of Quadrotors
Alexandre Didier, Anilkumar Parsi, Jeremy Coulson +1
Robust adaptive model predictive control (RAMPC) is a novel control method that combines robustness guarantees with respect to unknown parameters and bounded disturbances into a mo…