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Electronics and Electrical Engineering
Netherlands
2026

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
68
Citations
23409
World Ranking
994
National Ranking
9

Research.com Recognitions

  • 2026 - Research.com Electronics and Electrical Engineering in Netherlands Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in Netherlands Leader Award

Overview

Robert Babuska is affiliated with Delft University of Technology in the Netherlands. Their research spans multiple areas primarily within computer science and engineering, with an emphasis on robotics and intelligent systems.

The main fields of study covered by their work include:

  • Computer Science
  • Engineering

Their research focuses on several subfields, such as:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Aerospace Engineering
  • Statistical and Nonlinear Physics

The topics addressed in their publications include:

  • Evolutionary Algorithms and Applications
  • Reinforcement Learning in Robotics
  • Neural Networks and Applications
  • Robotic Path Planning Algorithms
  • Robotics and Sensor-Based Localization
  • Model Reduction and Neural Networks
  • Robot Manipulation and Learning

Among the recent papers authored or co-authored by Robert Babuska are:

  • Inclined Quadrotor Landing using Deep Reinforcement Learning, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Where to Look Next: Learning Viewpoint Recommendations for Informative Trajectory Planning, 2022, 2022 International Conference on Robotics and Automation (ICRA)
  • Multi-objective symbolic regression for physics-aware dynamic modeling, 2021, Expert Systems with Applications
  • Learning Assembly Tasks in a Few Minutes by Combining Impedance Control and Residual Recurrent Reinforcement Learning, 2021, Advanced Intelligent Systems
  • Learning 3D shape proprioception for continuum soft robots with multiple magnetic sensors, 2022, Soft Matter

Frequent co-authors collaborating with Babuska include:

  • Erik Derner
  • Jens Kober
  • Jiří Kubalík
  • Laura Ferranti
  • Cosimo Della Santina

Robert Babuska's work has appeared in several publication venues. Among the most frequent are:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • IEEE Access
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • 2022 International Conference on Robotics and Automation (ICRA)

Best Publications

  • A Comprehensive Survey of Multiagent Reinforcement Learning

    L. Busoniu;R. Babuska;B. De Schutter

  • Fuzzy Modeling for Control

    Robert Babuska

  • A Survey of Actor-Critic Reinforcement Learning: Standard and Natural Policy Gradients

    I. Grondman;L. Busoniu;G. A. D. Lopes;R. Babuska

  • Multi-agent Reinforcement Learning: An Overview

    Lucian Buşoniu;Robert Babuška;Bart De Schutter

  • Similarity measures in fuzzy rule base simplification

    M. Setnes;R. Babuska;U. Kaymak;H.R. van Nauta Lemke

  • Perspectives of fuzzy systems and control

    Antonio Sala;Thierry Marie Guerra;Robert Babuška

  • Neuro-fuzzy methods for nonlinear system identification

    Robert Babuska;Henk B. Verbruggen

  • Stability Analysis and Nonlinear Observer Design using Takagi-Sugeno Fuzzy Models

    Robert Babuska;Bart De Schutter;Zsfia Lendek;T. M. Guerra

  • Fuzzy model for the prediction of unconfined compressive strength of rock samples

    M Alvarez Grima;R Babuška

  • An overview of fuzzy modeling for control

    R. Babuška;H.B. Verbruggen

  • Modified Gath-Geva fuzzy clustering for identification of Takagi-Sugeno fuzzy models

    J. Abonyi;R. Babuska;F. Szeifert

  • Rule-based modeling: precision and transparency

    M. Setnes;R. Babuska;H.B. Verbruggen

  • Deep convolutional neural networks for detection of rail surface defects

    Shahrzad Faghih-Roohi;Siamak Hajizadeh;Alfredo Nunez;Robert Babuska

  • Residential Demand Response of Thermostatically Controlled Loads Using Batch Reinforcement Learning

    Frederik Ruelens;Bert J. Claessens;Stijn Vandael;Bart De Schutter

  • Railway Track Circuit Fault Diagnosis Using Recurrent Neural Networks

    Tim de Bruin;Kim Verbert;Robert Babuska

  • Experience Replay for Real-Time Reinforcement Learning Control

    S. Adam;L. Busoniu;R. Babuska

  • Multi-agent discrete-time graphical games and reinforcement learning solutions

    Mohammed I. Abouheaf;Frank L. Lewis;Kyriakos G. Vamvoudakis;Sofie Haesaert

  • Fuzzy Systems, Modeling and Identification

    Robert Babuška

  • Fuzzy predictive control applied to an air-conditioning system

    J.M. Sousa;R. Babuška;H.B. Verbruggen

  • Fuzzy model-based predictive control using Takagi-Sugeno models

    Johannes A. Roubos;Stanimir Mollov;Robert Babuska;Henk B. Verbruggen

Frequent Co-Authors

B. De Schutter
B. De Schutter Delft University of Technology
Damien Ernst
Damien Ernst University of Liège
Thierry Marie Guerra
Thierry Marie Guerra University Polytechnic Hauts-de-France
David Naso
David Naso Polytechnic University of Bari
Qiping Chu
Qiping Chu Delft University of Technology
Frank L. Lewis
Frank L. Lewis The University of Texas at Arlington
Tor Arne Johansen
Tor Arne Johansen Norwegian University of Science and Technology
Cesare Fantuzzi
Cesare Fantuzzi University of Modena and Reggio Emilia
Jan Mulder
Jan Mulder Broadcom (United States)
Michel Verhaegen
Michel Verhaegen Delft University of Technology

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