NEWS    New robotics benchmark system

Date released: November 16, 2020

  •  NEWS    New robotics benchmark system
  • Date:

    November 16, 2020

  • Description:

    MERL researchers, in collaboration with researchers from MELCO and the Department of Brain and Cognitive Science at MIT, have released simulation software Circular Maze Environment (CME). This system could be used as a new benchmark for evaluating different control and robot learning algorithms. The control objective in this system is to tip and the tilt the maze so as to drive one (or multiple) marble(s) to the innermost ring of the circular maze. Although the system is very intuitive for humans to control, it is very challenging for artificial intelligence agents to learn efficiently. It poses several challenges for both model-based as well as model-free methods, due to its non-smooth dynamics, long planning horizon, and non-linear dynamics. The released Python package provides the simulation environment for the circular maze, where movement of multiple marbles could be simulated simultaneously. The package also provides a trajectory optimization algorithm to design a model-based controller in simulation.


  • External Link:

    https://www.merl.com/research/license/CME

  • MERL Contacts:
  • Research Areas:

    Artificial Intelligence, Machine Learning, Robotics

    •  Paul, S., van Baar, J., Roy-Chowdhury, A.K., "Learning from Trajectories via Subgoal Discovery", Advances in Neural Information Processing Systems (NeurIPS), pp. 8409-8419, October 2019.
      BibTeX TR2019-128 PDF
      • @article{Paul2019oct,
      • author = {Paul, Sujoy and van Baar, Jeroen and Roy-Chowdhury, Amit K.},
      • title = {Learning from Trajectories via Subgoal Discovery},
      • journal = {Advances in Neural Information Processing Systems (NeurIPS)},
      • year = 2019,
      • pages = {8409--8419},
      • month = oct,
      • url = {https://www.merl.com/publications/TR2019-128}
      • }
    •  Romeres, D., Jha, D.K., Dalla Libera, A., Yerazunis, W.S., Nikovski, D.N., "Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/​ICRA.2019.8794229, May 2019, pp. 3195-3202.
      BibTeX TR2019-028 PDF Video Software
      • @inproceedings{Romeres2019may,
      • author = {Romeres, Diego and Jha, Devesh K. and Dalla Libera, Alberto and Yerazunis, William S. and Nikovski, Daniel N.},
      • title = {Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze},
      • booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
      • year = 2019,
      • pages = {3195--3202},
      • month = may,
      • publisher = {IEEE},
      • doi = {10.1109/ICRA.2019.8794229},
      • issn = {2577-087X},
      • isbn = {978-1-5386-6027-0},
      • url = {https://www.merl.com/publications/TR2019-028}
      • }
    •  van Baar, J., Sullivan, A., Corcodel, R., Jha, D.K., Romeres, D., Nikovski, D.N., "Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/​ICRA.2019.8793561, May 2019, pp. 6001-6007.
      BibTeX TR2018-202 PDF Video Software
      • @inproceedings{vanBaar2019may,
      • author = {van Baar, Jeroen and Sullivan, Alan and Corcodel, Radu and Jha, Devesh K. and Romeres, Diego and Nikovski, Daniel N.},
      • title = {Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics},
      • booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
      • year = 2019,
      • pages = {6001--6007},
      • month = may,
      • doi = {10.1109/ICRA.2019.8793561},
      • url = {https://www.merl.com/publications/TR2018-202}
      • }