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07/10/2023
Episodic Gaussian Process-Based Learning Control with Vanishing Tracking Errors
Due to the increasing complexity of technical systems, accurate first pr...
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05/25/2023
Koopman Kernel Regression
Many machine learning approaches for decision making, such as reinforcem...
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05/14/2023
Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning
When the dynamics of systems are unknown, supervised machine learning te...
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04/21/2023
Time Series Classification for Detecting Parkinson's Disease from Wrist Motions
Parkinson's disease (PD) is a neurodegenerative disease with frequently ...
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04/12/2023
Distributed Coverage Control of Constrained Constant-Speed Unicycle Multi-Agent Systems
This paper proposes a novel distributed coverage controller for a multi-...
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03/31/2023
Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States
As control engineering methods are applied to increasingly complex syste...
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02/23/2023
Sharp Calibrated Gaussian Processes
While Gaussian processes are a mainstay for various engineering and scie...
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02/12/2023
Variational Integrators and Graph-Based Solvers for Multibody Dynamics in Maximal Coordinates
Multibody dynamics simulators are an important tool in many fields, incl...
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12/01/2022
Safe Learning-Based Control of Elastic Joint Robots via Control Barrier Functions
Ensuring safety is of paramount importance in physical human-robot inter...
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09/14/2022
Uncertainty-Aware Visual Perception for Safe Motion Planning
For safe operation, a robot must be able to avoid collisions in uncertai...
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07/04/2022
Safe Reinforcement Learning via Confidence-Based Filters
Ensuring safety is a crucial challenge when deploying reinforcement lear...
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06/28/2022
Dext-Gen: Dexterous Grasping in Sparse Reward Environments with Full Orientation Control
Reinforcement learning is a promising method for robotic grasping as it ...
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06/24/2022
Physically Consistent Learning of Conservative Lagrangian Systems with Gaussian Processes
This paper proposes a physically consistent Gaussian Process (GP) enabli...
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02/23/2022
Networked Online Learning for Control of Safety-Critical Resource-Constrained Systems based on Gaussian Processes
Safety-critical technical systems operating in unknown environments requ...
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01/27/2022
Towards Data-driven LQR with KoopmanizingFlows
We propose a novel framework for learning linear time-invariant (LTI) mo...
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12/10/2021
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators
Gaussian process regression is often applied for learning unknown system...
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12/08/2021
KoopmanizingFlows: Diffeomorphically Learning Stable Koopman Operators
We propose a novel framework for constructing linear time-invariant (LTI...
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11/05/2021
Adaptive Low-Pass Filtering using Sliding Window Gaussian Processes
When signals are measured through physical sensors, they are perturbed b...
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10/15/2021
Learning the Koopman Eigendecomposition: A Diffeomorphic Approach
We present a novel data-driven approach for learning linear representati...
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10/01/2021
Personalized Rehabilitation Robotics based on Online Learning Control
The use of rehabilitation robotics in clinical applications gains increa...
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09/15/2021
Linear-Time Contact and Friction Dynamics in Maximal Coordinates using Variational Integrators
Simulation of contact and friction dynamics is an important basis for co...
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09/06/2021
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications
Gaussian processes have become a promising tool for various safety-criti...
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07/30/2021
Distributed Event- and Self-Triggered Coverage Control with Speed Constrained Unicycle Robots
Voronoi coverage control is a particular problem of importance in the ar...
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05/25/2021
Gaussian Process-based Stochastic Model Predictive Control for Overtaking in Autonomous Racing
A fundamental aspect of racing is overtaking other race cars. Whereas pr...
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04/09/2021
Inverse Reinforcement Learning a Control Lyapunov Approach
Inferring the intent of an intelligent agent from demonstrations and sub...
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04/09/2021
Distributed Bayesian Online Learning for Cooperative Manipulation
For tasks where the dynamics of multiple agents are physically coupled, ...
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01/13/2021
Uniform Error and Posterior Variance Bounds for Gaussian Process Regression with Application to Safe Control
In application areas where data generation is expensive, Gaussian proces...
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11/20/2020
The Value of Data in Learning-Based Control for Training Subset Selection
Despite the existence of formal guarantees for learning-based control ap...
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11/17/2020
Fisher Information of a Family of Generalized Normal Distributions
In this brief note we compute the Fisher information of a family of gene...
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10/06/2020
Real-time Uncertainty Decomposition for Online Learning Control
Safety-critical decisions based on machine learning models require a cle...
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09/14/2020
Safe learning-based trajectory tracking for underactuated vehicles with partially unknown dynamics
Underactuated vehicles have gained much attention in the recent years du...
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07/24/2020
Anticipating the Long-Term Effect of Online Learning in Control
Control schemes that learn using measurement data collected online are i...
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06/25/2020
Prediction with Gaussian Process Dynamical Models
The modeling and simulation of dynamical systems is a necessary step for...
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06/16/2020
Real-Time Regression with Dividing Local Gaussian Processes
The increased demand for online prediction and the growing availability ...
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06/14/2020
GP3: A Sampling-based Analysis Framework for Gaussian Processes
Although machine learning is increasingly applied in control approaches,...
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06/14/2020
Learning Stable Nonparametric Dynamical Systems with Gaussian Process Regression
Modelling real world systems involving humans such as biological process...
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05/25/2020
How Training Data Impacts Performance in Learning-based Control
When first principle models cannot be derived due to the complexity of t...
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05/05/2020
AoI-based Finite Horizon Scheduling for Heterogeneous Networked Control Systems
Age of information (AoI) measures information freshness at the receiver....
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05/04/2020
Localized active learning of Gaussian process state space models
The performance of learning-based control techniques crucially depends o...
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09/12/2019
Closed-loop Model Selection for Kernel-based Models using Bayesian Optimization
Kernel-based nonparametric models have become very attractive for model-...
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06/25/2019
Keep soft robots soft -- a data-driven based trade-off between feed-forward and feedback control
Tracking control for soft robots is challenging due to uncertainties in ...
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06/04/2019
Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves
The posterior variance of Gaussian processes is a valuable measure of th...
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06/04/2019
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
Data-driven models are subject to model errors due to limited and noisy ...
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03/13/2019
Age-of-Information vs. Value-of-Information Scheduling for Cellular Networked Control Systems
Age-of-Information (AoI) is a recently introduced metric for network ope...
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12/18/2018
Value of Information in Feedback Control
In this article, we investigate the impact of information on networked c...
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11/16/2018
Mean Square Prediction Error of Misspecified Gaussian Process Models
Nonparametric modeling approaches show very promising results in the are...
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09/20/2018
Fully distributed cooperation for networked uncertain mobile manipulators
This paper investigates the fully distributed cooperation scheme for net...
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08/31/2018
A Multi-layer Gaussian Process for Motor Symptom Estimation in People with Parkinson's Disease
The assessment of Parkinson's disease (PD) poses a significant challenge...
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08/08/2018
Parkinson's Disease Assessment from a Wrist-Worn Wearable Sensor in Free-Living Conditions: Deep Ensemble Learning and Visualization
Parkinson's Disease (PD) is characterized by disorders in motor function...
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06/19/2018