People - Diego Romeres | Mitsubishi Electric Research Laboratories

Biography

Diego's research interests are in machine learning, system identification and robotic applications. At MERL he is currently working on applying nonparametric machine learning techniques for the control of robotic platforms. His Ph.D. thesis is about the combination of nonparametric data-driven models and physics-based models in gaussian processes for robot dynamics learning.
Recent News & Events
- NEWS Diego Romeres serves on the Programme Committee for the Conference on Innovative Applications of Artificial Intelligence, 2021.
  Date: February 4, 2021
  Where: N/A
  MERL Contact: Diego Romeres
  Research Areas: Artificial Intelligence, Data Analytics, Machine Learning
  Brief
  - Dr. Diego Romeres, Principal Research Scientist in the Data Analytics group, will serve on the Programme Committee for the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2021.
- NEWS Diego Romeres gave an invited talk on modeling and control of physical systems at the MIT workshop "ICRAxMIT"
  Date: June 9, 2020
  Where: ICRAxMIT
  MERL Contact: Diego Romeres
  Research Areas: Artificial Intelligence, Data Analytics, Dynamical Systems, Machine Learning, Robotics
  Brief
  - Diego Romeres, a Principal Research Scientist in MERL's Data Analytics group, gave an invited talk at the workshop ICRAxMIT organized at MIT. The talk briefly described a derivative-free framework that doesn't take in consideration velocities and accelerations to model and control robotic systems. The proposed approach is validated in two real robotic systems.
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MERL Publications
- Romeres, D., Liu, Y., Jha, D., Nikovski, D.N., "Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks", Robotics: Science and Systems, July 2020.
  BibTeX TR2020-110 PDF
  - @inproceedings{Romeres2020jul,
  - author = {Romeres, Diego and Liu, Yifang and Jha, Devesh and Nikovski, Daniel N.},
  - title = {Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks},
  - booktitle = {Robotics: Science and Systems},
  - year = 2020,
  - month = jul,
  - url = {https://www.merl.com/publications/TR2020-110}
  - }
- Jha, D., Kolaric, P., Raghunathan, A., Lewis, F., Benosman, M., Romeres, D., Nikovski, D.N., "Local Policy Optimization for Trajectory-Centric Reinforcement Learning", IEEE International Conference on Robotics and Automation (ICRA), Ayanna Howard, Eds., May 2020, pp. 5094-5100.
  BibTeX TR2020-062 PDF
  - @inproceedings{Jha2020may,
  - author = {Jha, Devesh and Kolaric, Patrik and Raghunathan, Arvind and Lewis, Frank and Benosman, Mouhacine and Romeres, Diego and Nikovski, Daniel N.},
  - title = {Local Policy Optimization for Trajectory-Centric Reinforcement Learning},
  - booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  - year = 2020,
  - editor = {Ayanna Howard},
  - pages = {5094--5100},
  - month = may,
  - publisher = {IEEE},
  - isbn = {978-1-7281-7395-5},
  - url = {https://www.merl.com/publications/TR2020-062}
  - }
- Romeres, D., Dalla Libera, A., Jha, D., Yerazunis, W.S., Nikovski, D.N., "Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements", Robotics and Automation Letters, DOI: 10.1109/LRA.2020.2977255, Vol. 5, No. 2, pp. 3548-3555, May 2020.
  BibTeX TR2020-063 PDF
  - @article{Romeres2020may,
  - author = {Romeres, Diego and Dalla Libera, Alberto and Jha, Devesh and Yerazunis, William S. and Nikovski, Daniel N.},
  - title = {Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements},
  - journal = {Robotics and Automation Letters},
  - year = 2020,
  - volume = 5,
  - number = 2,
  - pages = {3548--3555},
  - month = may,
  - doi = {10.1109/LRA.2020.2977255},
  - issn = {2377-3766},
  - url = {https://www.merl.com/publications/TR2020-063}
  - }
- Romeres, D., Dalla Libera, A., Jha, D., Yerazunis, W.S., Nikovski, D.N., "Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements", arXiv, DOI: 10.1109/LRA.2020.2977255, February 2020.
  BibTeX arXiv
  - @article{Romeres2020feb,
  - author = {Romeres, Diego and Dalla Libera, Alberto and Jha, Devesh and Yerazunis, William S. and Nikovski, Daniel N.},
  - title = {Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements},
  - journal = {arXiv},
  - year = 2020,
  - month = feb,
  - doi = {10.1109/LRA.2020.2977255},
  - issn = {2377-3766},
  - url = {https://arxiv.org/abs/2002.10621}
  - }
- Jha, D., Kolaric, P., Romeres, D., Raghunathan, A., Benosman, M., Nikovski, D.N., "Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning", NeurIPS Workshop on Safety and Robustness in Decision Making, December 2019.
  BibTeX TR2019-156 PDF
  - @inproceedings{Jha2019dec2,
  - author = {Jha, Devesh and Kolaric, Patrik and Romeres, Diego and Raghunathan, Arvind and Benosman, Mouhacine and Nikovski, Daniel N.},
  - title = {Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning},
  - booktitle = {NeurIPS Workshop on Safety and Robustness in Decision Making},
  - year = 2019,
  - month = dec,
  - url = {https://www.merl.com/publications/TR2019-156}
  - }
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Other Publications
- Diego Romeres, Giulia Prando, Gianluigi Pillonetto and Alessandro Chiuso, "On-line bayesian system identification", Control Conference (ECC), 2016 European, 2016, pp. 1359-1364.
  BibTeX
  - @Inproceedings{romeres2016line,
  - author = {Romeres, Diego and Prando, Giulia and Pillonetto, Gianluigi and Chiuso, Alessandro},
  - title = {On-line bayesian system identification},
  - booktitle = {Control Conference (ECC), 2016 European},
  - year = 2016,
  - pages = {1359--1364},
  - organization = {IEEE}
  - }
- Diego Romeres, Mattia Zorzi, Raffaello Camoriano and Alessandro Chiuso, "Online semi-parametric learning for inverse dynamics modeling", Decision and Control (CDC), 2016 IEEE 55th Conference on, 2016, pp. 2945-2950.
  BibTeX
  - @Inproceedings{romeres2016online,
  - author = {Romeres, Diego and Zorzi, Mattia and Camoriano, Raffaello and Chiuso, Alessandro},
  - title = {Online semi-parametric learning for inverse dynamics modeling},
  - booktitle = {Decision and Control (CDC), 2016 IEEE 55th Conference on},
  - year = 2016,
  - pages = {2945--2950},
  - organization = {IEEE}
  - }
- Diego Romeres, Mattia Zorzi, Raffaello Camoriano and Alessandro Chiuso, "Online semi-parametric learning for inverse dynamics modeling", Decision and Control (CDC), 2016 IEEE 55th Conference on, 2016, pp. 2945-2950.
  BibTeX
  - @Inproceedings{romeres2016onlinesemiparametric,
  - author = {Romeres, Diego and Zorzi, Mattia and Camoriano, Raffaello and Chiuso, Alessandro},
  - title = {Online semi-parametric learning for inverse dynamics modeling},
  - booktitle = {Decision and Control (CDC), 2016 IEEE 55th Conference on},
  - year = 2016,
  - pages = {2945--2950},
  - organization = {IEEE}
  - }
- Giulia Prando, Diego Romeres, Gianluigi Pillonetto and Alessandro Chiuso, "Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets", Control Conference (ECC), 2016 European, 2016, pp. 1365-1370.
  BibTeX
  - @Inproceedings{tprando2016classical,
  - author = {Prando, Giulia and Romeres, Diego and Pillonetto, Gianluigi and Chiuso, Alessandro},
  - title = {Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets},
  - booktitle = {Control Conference (ECC), 2016 European},
  - year = 2016,
  - pages = {1365--1370},
  - organization = {IEEE}
  - }
- Giulia Prando, Diego Romeres and Alessandro Chiuso, "Online identification of time-varying systems: A Bayesian approach", Decision and Control (CDC), 2016 IEEE 55th Conference on, 2016, pp. 3775-3780.
  BibTeX
  - @Inproceedings{tprando2016online,
  - author = {Prando, Giulia and Romeres, Diego and Chiuso, Alessandro},
  - title = {Online identification of time-varying systems: A Bayesian approach},
  - booktitle = {Decision and Control (CDC), 2016 IEEE 55th Conference on},
  - year = 2016,
  - pages = {3775--3780},
  - organization = {IEEE}
  - }
- Ulrich Muenz and Diego Romeres, "Region of attraction of power systems", IFAC Proceedings Volumes, Vol. 46, No. 27, pp. 49-54, 2013.
  BibTeX
  - @Article{munz2013region,
  - author = {Muenz, Ulrich and Romeres, Diego},
  - title = {Region of attraction of power systems},
  - journal = {IFAC Proceedings Volumes},
  - year = 2013,
  - volume = 46,
  - number = 27,
  - pages = {49--54},
  - publisher = {Elsevier}
  - }
- Diego Romeres, Florian Doerfler and Francesco Bullo, "Novel results on slow coherency in consensus and power networks", Control Conference (ECC), 2013 European, 2013, pp. 742-747.
  BibTeX
  - @Inproceedings{romeres2013novel,
  - author = {Romeres, Diego and Doerfler, Florian and Bullo, Francesco},
  - title = {Novel results on slow coherency in consensus and power networks},
  - booktitle = {Control Conference (ECC), 2013 European},
  - year = 2013,
  - pages = {742--747},
  - organization = {IEEE}
  - }
- Saverio Bolognani, Andrea Carron, Alberto Di Vittorio, Diego Romeres, Luca Schenato and Sandro Zampieri, "Distributed multi-hop reactive power compensation in smart micro-grids subject to saturation constraints", Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, 2012, pp. 1118-1123.
  BibTeX
  - @Inproceedings{bolognani2012distributed,
  - author = {Bolognani, Saverio and Carron, Andrea and Di Vittorio, Alberto and Romeres, Diego and Schenato, Luca and Zampieri, Sandro},
  - title = {Distributed multi-hop reactive power compensation in smart micro-grids subject to saturation constraints},
  - booktitle = {Decision and Control (CDC), 2012 IEEE 51st Annual Conference on},
  - year = 2012,
  - pages = {1118--1123},
  - organization = {IEEE}
  - }
Software Downloads
- Quasi-Newton Trust Region Policy Optimization

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Software Downloads

Quasi-Newton Trust Region Policy Optimization