AWARD    University of Padua and MERL team wins the AI Olympics with RealAIGym competition at IROS24

Date released: October 25, 2024

  •  AWARD    University of Padua and MERL team wins the AI Olympics with RealAIGym competition at IROS24
  • Date:

    October 17, 2024

  • Awarded to:

    Niccolò Turcato, Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli, Diego Romeres

  • Description:

    The team composed of the control group at the University of Padua and MERL's Optimization and Robotic team ranked 1st out of the 4 finalist teams that arrived to the 2nd AI Olympics with RealAIGym competition at IROS 24, which focused on control of under-actuated robots. The team was composed by Niccolò Turcato, Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli and Diego Romeres. The competition was organized by the German Research Center for Artificial Intelligence (DFKI), Technical University of Darmstadt and Chalmers University of Technology.

    The competition and award ceremony was hosted by IEEE International Conference on Intelligent Robots and Systems (IROS) on October 17, 2024 in Abu Dhabi, UAE. Diego Romeres presented the team's method, based on a model-based reinforcement learning algorithm called MC-PILCO.

  • MERL Contact:
  • External Link:

    https://ai-olympics.dfki-bremen.de

  • Research Areas:

    Artificial Intelligence, Dynamical Systems, Machine Learning, Robotics

    •  Dalla Libera, A., Turcato, N., Giacomuzzo, G., Carli, R., Romeres, D., "Learning control of underactuated double pendulum with Model-Based Reinforcement Learning", Competition: AI Olympics With RealAIGym, October 2024.
      BibTeX TR2024-142 PDF
      • @inproceedings{DallaLibera2024oct,
      • author = {Dalla Libera, Alberto and Turcato, Niccolò and Giacomuzzo, Giulio and Carli, Ruggero and Romeres, Diego}},
      • title = {Learning control of underactuated double pendulum with Model-Based Reinforcement Learning},
      • booktitle = {Competition: AI Olympics With RealAIGym},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-142}
      • }
    •  Amadio, F., Dalla Libera, A., Antonello, R., Nikovski, D.N., Carli, R., Romeres, D., "Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application", IEEE Transaction on Robotics, DOI: 10.1109/​TRO.2022.3184837, Vol. 38, No. 6, pp. 3879-3898, December 2022.
      BibTeX TR2022-154 PDF Videos Software
      • @article{Romeres2022dec,
      • author = {Amadio, Fabio and Dalla Libera, Alberto and Antonello, Riccardo and Nikovski, Daniel N. and Carli, Ruggero and Romeres, Diego},
      • title = {Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application},
      • journal = {IEEE Transaction on Robotics},
      • year = 2022,
      • volume = 38,
      • number = 6,
      • pages = {3879--3898},
      • month = dec,
      • doi = {10.1109/TRO.2022.3184837},
      • issn = {1941-0468},
      • url = {https://www.merl.com/publications/TR2022-154}
      • }