Search Results for author: Angela P. Schoellig

Found 33 papers, 13 papers with code

Is Data All That Matters? The Role of Control Frequency for Learning-Based Sampled-Data Control of Uncertain Systems

1 code implementation14 Mar 2024 Ralf Römer, Lukas Brunke, SiQi Zhou, Angela P. Schoellig

While a strong focus has been placed on increasing the amount and quality of data to improve performance, data can never fully eliminate uncertainty, making feedback necessary to ensure stability and performance.

Gaussian Processes

Optimized Control Invariance Conditions for Uncertain Input-Constrained Nonlinear Control Systems

no code implementations15 Dec 2023 Lukas Brunke, SiQi Zhou, Mingxuan Che, Angela P. Schoellig

We demonstrate the efficacy of our proposed approach in simulation and real-world experiments on a quadrotor and show that we can achieve safe closed-loop behavior for a learned system while satisfying state and input constraints.

Multi-Step Model Predictive Safety Filters: Reducing Chattering by Increasing the Prediction Horizon

1 code implementation20 Sep 2023 Federico Pizarro Bejarano, Lukas Brunke, Angela P. Schoellig

In experiments with a Crazyflie 2. 0 drone, we show that, in addition to preserving the desired safety guarantees, the proposed MPSF reduces chattering by more than a factor of 4 compared to previous MPSF formulations.

Model Predictive Control

Uncertainty-aware 3D Object-Level Mapping with Deep Shape Priors

no code implementations17 Sep 2023 Ziwei Liao, Jun Yang, Jingxing Qian, Angela P. Schoellig, Steven L. Waslander

Unlike current state-of-the-art approaches, we explicitly model the uncertainty of the object shapes and poses during our optimization, resulting in a high-quality object-level mapping system.

3D Reconstruction Object

What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities

1 code implementation19 Aug 2023 SiQi Zhou, Lukas Brunke, Allen Tao, Adam W. Hall, Federico Pizarro Bejarano, Jacopo Panerati, Angela P. Schoellig

Open-sourcing research publications is a key enabler for the reproducibility of studies and the collective scientific progress of a research community.

Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety Filter

1 code implementation20 Jul 2023 Adam W. Hall, Melissa Greeff, Angela P. Schoellig

This safety filter is then used to refine inputs from a flat model predictive controller to perform constrained nonlinear learning-based optimal control through two successive convex optimizations.

Computational Efficiency Model Predictive Control

Multi-View Keypoints for Reliable 6D Object Pose Estimation

no code implementations29 Mar 2023 Alan Li, Angela P. Schoellig

6D Object pose estimation is a fundamental component in robotics enabling efficient interaction with the environment.

6D Pose Estimation using RGB Object

Robust Predictive Output-Feedback Safety Filter for Uncertain Nonlinear Control Systems

1 code implementation17 Dec 2022 Lukas Brunke, SiQi Zhou, Angela P. Schoellig

Recently, we have seen an increasing number of learning-based control algorithms developed to address the challenge of decision making under dynamics uncertainties.

Decision Making

Bridging the Model-Reality Gap with Lipschitz Network Adaptation

no code implementations7 Dec 2021 SiQi Zhou, Karime Pereida, Wenda Zhao, Angela P. Schoellig

In particular, we present a learning-based model reference adaptation approach that makes a robot system, with possibly uncertain dynamics, behave as a predefined reference model.

safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in Robotics

4 code implementations13 Sep 2021 Zhaocong Yuan, Adam W. Hall, SiQi Zhou, Lukas Brunke, Melissa Greeff, Jacopo Panerati, Angela P. Schoellig

In recent years, both reinforcement learning and learning-based control -- as well as the study of their safety, which is crucial for deployment in real-world robots -- have gained significant traction.

reinforcement-learning Reinforcement Learning (RL)

Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning

4 code implementations13 Aug 2021 Lukas Brunke, Melissa Greeff, Adam W. Hall, Zhaocong Yuan, SiQi Zhou, Jacopo Panerati, Angela P. Schoellig

The last half-decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learning communities.

Decision Making reinforcement-learning +2

Learning-based Bias Correction for Time Difference of Arrival Ultra-wideband Localization of Resource-constrained Mobile Robots

1 code implementation2 Mar 2021 Wenda Zhao, Jacopo Panerati, Angela P. Schoellig

Accurate indoor localization is a crucial enabling technology for many robotics applications, from warehouse management to monitoring tasks.

Indoor Localization Management

Experience Selection Using Dynamics Similarity for Efficient Multi-Source Transfer Learning Between Robots

no code implementations29 Mar 2020 Michael J. Sorocky, Siqi Zhou, Angela P. Schoellig

We show that selecting experiences based on the proposed similarity metric effectively facilitates the learning of the target quadrotor, improving performance by 62% compared to a poorly selected experience.

Transfer Learning

Variational Inference with Parameter Learning Applied to Vehicle Trajectory Estimation

no code implementations21 Mar 2020 Jeremy N. Wong, David J. Yoon, Angela P. Schoellig, Timothy D. Barfoot

Our contribution is to additionally learn parameters of our system models (which may be difficult to choose in practice) within the ESGVI framework.

Variational Inference

Learning-based Bias Correction for Ultra-wideband Localization of Resource-constrained Mobile Robots

no code implementations20 Mar 2020 Wenda Zhao, Abhishek Goudar, Jacopo Panerati, Angela P. Schoellig

Accurate indoor localization is a crucial enabling technology for many robotics applications, from warehouse management to monitoring tasks.

Indoor Localization Management

An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants

no code implementations24 Dec 2019 SiQi Zhou, Angela P. Schoellig

We consider this work to be a step towards understanding the expressive power of DNNs and towards designing appropriate deep architectures for practical applications such as system control.

Image Classification

No-Regret Bayesian Optimization with Unknown Hyperparameters

no code implementations10 Jan 2019 Felix Berkenkamp, Angela P. Schoellig, Andreas Krause

In this paper, we present the first BO algorithm that is provably no-regret and converges to the optimum without knowledge of the hyperparameters.

Bayesian Optimization

Provably Robust Learning-Based Approach for High-Accuracy Tracking Control of Lagrangian Systems

no code implementations3 Apr 2018 Mohamed K. Helwa, Adam Heins, Angela P. Schoellig

Inverse dynamics control and feedforward linearization techniques are typically used to convert the complex nonlinear dynamics of Lagrangian systems to a set of decoupled double integrators, and then a standard, outer-loop controller can be used to calculate the commanded acceleration for the linearized system.

Gaussian Processes

Learning of Coordination Policies for Robotic Swarms

no code implementations19 Sep 2017 Qiyang Li, Xintong Du, Yizhou Huang, Quinlan Sykora, Angela P. Schoellig

Inspired by biological swarms, robotic swarms are envisioned to solve real-world problems that are difficult for individual agents.

An Inversion-Based Learning Approach for Improving Impromptu Trajectory Tracking of Robots with Non-Minimum Phase Dynamics

no code implementations13 Sep 2017 Siqi Zhou, Mohamed K. Helwa, Angela P. Schoellig

This paper presents a learning-based approach for impromptu trajectory tracking for non-minimum phase systems, i. e., systems with unstable inverse dynamics.

Multi-Robot Transfer Learning: A Dynamical System Perspective

no code implementations27 Jul 2017 Mohamed K. Helwa, Angela P. Schoellig

In this paper, we investigate, through a theoretical study of single-input single-output (SISO) systems, the properties of such optimal transfer maps.

Transfer Learning

Deep Neural Networks for Improved, Impromptu Trajectory Tracking of Quadrotors

no code implementations20 Oct 2016 Qiyang Li, Jingxing Qian, Zining Zhu, Xuchan Bao, Mohamed K. Helwa, Angela P. Schoellig

Trajectory tracking control for quadrotors is important for applications ranging from surveying and inspection, to film making.

Unity

A real-time analysis of rock fragmentation using UAV technology

no code implementations14 Jul 2016 Thomas Bamford, Kamran Esmaeili, Angela P. Schoellig

The pile was photographed by a camera attached to the UAV, and the particle size distribution curves were generated in almost real-time.

Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics

3 code implementations14 Feb 2016 Felix Berkenkamp, Andreas Krause, Angela P. Schoellig

While an initial guess for the parameters may be obtained from dynamic models of the robot, parameters are usually tuned manually on the real system to achieve the best performance.

Bayesian Optimization

Safe Controller Optimization for Quadrotors with Gaussian Processes

3 code implementations3 Sep 2015 Felix Berkenkamp, Angela P. Schoellig, Andreas Krause

One of the most fundamental problems when designing controllers for dynamic systems is the tuning of the controller parameters.

Robotics

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