$$ % Define your custom commands here \newcommand{\bmat}[1]{\begin{bmatrix}#1\end{bmatrix}} \newcommand{\E}{\mathbb{E}} \newcommand{\P}{\mathbb{P}} \newcommand{\S}{\mathbb{S}} \newcommand{\R}{\mathbb{R}} \newcommand{\S}{\mathbb{S}} \newcommand{\norm}[2]{\|{#1}\|_{{}_{#2}}} \newcommand{\pd}[2]{\frac{\partial #1}{\partial #2}} \newcommand{\pdd}[2]{\frac{\partial^2 #1}{\partial #2^2}} \newcommand{\vectornorm}[1]{\left|\left|#1\right|\right|} \newcommand{\abs}[1]{\left|{#1}\right|} \newcommand{\mbf}[1]{\mathbf{#1}} \newcommand{\mc}[1]{\mathcal{#1}} \newcommand{\bm}[1]{\boldsymbol{#1}} \newcommand{\nicefrac}[2]{{}^{#1}\!/_{\!#2}} \newcommand{\argmin}{\operatorname*{arg\,min}} \newcommand{\argmax}{\operatorname*{arg\,max}} \newcommand{\dd}{\operatorname{d}\!} $$

Aykut C. Satici

Associate Professor of Systems Engineering at UT Dallas. Robotics, nonlinear control, and machine learning.

THE UNIVERSITY OF TEXAS AT DALLAS

Aykut C. Satici

Associate Professor of Systems Engineering

Erik Jonsson School of Engineering and Computer Science

I study robotics, nonlinear control, and machine learning. My research combines mathematical models, optimization, and learning to understand and control robotic systems, with applications in locomotion and manipulation. I lead Robot Control Lab at UT Dallas.

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LAB NEWS

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RESEARCH

Mathematics, dynamics, and learning

Robotics

Locomotion and manipulation in robotic systems, with an emphasis on using their natural dynamics.

Robotics and control →

Nonlinear control

Energy shaping and passivity-based methods for controlling underactuated mechanical systems.

Selected work →

Machine learning

Data-driven control design, neural models, and Bayesian approaches to uncertainty and robustness.

Robust machine learning →

SELECTED WORK

A closer look at the research

2023

Data-Driven Passivity-Based Control of Underactuated Mechanical Systems via Interconnection and Damping Assignment

Google Scholar

Wankun Sirichotiyakul and Aykut C. Satici

International Journal of Control

2023

Controlling UAVs by Sensing the Electric or the Magnetic Field Around Power Lines

Google Scholar

Aykut C. Satici, Alex Peterson, John Chiasson, and Zachary Adams

IEEE Control Systems Letters

2016

A coordinate-free framework for robotic pizza tossing and catching

Google Scholar

Aykut C. Satici, Fabio Ruggiero, Vincenzo Lippiello, and Bruno Siciliano

IEEE International Conference on Robotics and Automation (ICRA)

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RESEARCH GROUP

Robot Control Lab

Our group conducts foundational research in robotics, nonlinear control, and machine learning, drawing on Bayesian statistics, optimization, and algebraic and differential geometry.

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TEACHING

Learning through models and systems

Course materials in robotics, optimization, deep learning, system modeling and control, and systems architecture.

Deep learning System modeling and control Systems architecture

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