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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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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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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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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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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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10/01/2021
Personalized Rehabilitation Robotics based on Online Learning Control
The use of rehabilitation robotics in clinical applications gains increa...
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09/06/2021
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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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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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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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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05/04/2020
Localized active learning of Gaussian process state space models
The performance of learning-based control techniques crucially depends o...
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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