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Floris Van Breugel

Mechanical Engineering

Open to new collaborations

Research interests

We study insects for inspiration in designing robust and novel control systems for robots. Our lab uses real-time tracking, high speed video, and virtual reality to study freely moving animals. Then, aided by modern machine learning tools and control theory, we analyze the behavior, and implement the principles on robotic systems. Along the way, we use genetic tools available in the fruit fly to gain insight into how brains function.

Recent publications

The ten most recent from their Google Scholar profile, newest first.

  1. Wind history shapes olfactory search response in free flying Drosophila melanogaster

    J Houle, AP Lopez, F van Breugel. Journal of Experimental Biology, jeb. 252635 , 2026. 2026

    1 citation

  2. Central complex representations of self-movement are sufficient to compute wind direction in flight

    CE May, B Cellini, SD Stupski, AP Lopez, N Mangat, F van Breugel, .... Science Advances 12 (35), eaeh7220 , 2026. 2026

    1 citation

  3. Vespula pensylvanica locate odour sources across diverse natural wind conditions

    F Houle, Jaleesa and van Breugel. Biology Letters 22 (1), 20250603 , 2026. 2026

  4. Duality of Stochastic Observability and Constructability and Links to Fisher Information

    B Boyacıoğlu, F van Breugel. IEEE Control Systems Letters 8, 3458-3463 , 2025. 2025

    5 citations

  5. A compact multisensory representation of self-motion is sufficient for computing an external world variable

    CE May, B Cellini, F van Breugel, KI Nagel. bioRxiv , 2025. 2025

    5 citations

  6. Vespula pensylvanica locate odor sources across diverse natural wind conditions

    J Houle, F van Breugel. bioRxiv, 2025.10. 01.679804 , 2025. 2025

    3 citations

  7. COSMOS: A Data-Driven Approach to Simulating Odor Encounters for Agents Moving Through Chemical Plumes of Various Scales

    A Nag, F Van Breugel. IEEE Access 13, 189216-189224 , 2025. 2025

  8. Discovering and exploiting active sensing motifs for estimation

    B Cellini, B Boyacioglu, A Lopez, F van Breugel. arXiv preprint arXiv:2511.08766 , 2025. 2025

  9. A Taxonomy of Numerical Differentiation Methods

    P Komarov, F van Breugel, JN Kutz. arXiv preprint arXiv:2512.09090 , 2025. 2025

  10. Data Driven Estimation Techniques for Modeling Available Aircraft Thrust During Engine Malfunction Emergencies

    JM Peterson, F van Breugel, R LeClair. AIAA SCITECH 2025 Forum, 2012 , 2025. 2025

All publications on Google Scholar