TR2024-142

Learning control of underactuated double pendulum with Model-Based Reinforcement Learning

    •  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}
      • }
  • MERL Contact:
  • Research Areas:

    Machine Learning, Robotics

Abstract:

This report describes our proposed solution for the second AI Olympics competition held at IROS 2024. Our solution is based on a recent Model-Based Reinforcement Learning algorithm named MC-PILCO. Besides briefly reviewing the algorithm, we discuss the most critical aspects of the MC- PILCO implementation in the tasks at hand.

 

  • Related News & Events

    •  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
      MERL Contact: Diego Romeres
      Research Areas: Artificial Intelligence, Dynamical Systems, Machine Learning, Robotics
      Brief
      • 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.
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  • Related Publication

  •  Turcato, N., Dalla Libera, A., Giacomuzzo, G., Carli, R., Romeres, D., "Learning control of underactuated double pendulum with Model-Based Reinforcement Learning", arXiv, September 2024.
    BibTeX arXiv
    • @article{Turcato2024sep,
    • author = {Turcato, Niccolò and Dalla Libera, Alberto and Giacomuzzo, Giulio and Carli, Ruggero and Romeres, Diego}},
    • title = {Learning control of underactuated double pendulum with Model-Based Reinforcement Learning},
    • journal = {arXiv},
    • year = 2024,
    • month = sep,
    • url = {https://arxiv.org/abs/2409.05811}
    • }