NEWS    Karl Berntorp gave Spotlight Talk at CDC Workshop on Gaussian Process Learning-Based Control

Date released: December 6, 2022


  •  NEWS    Karl Berntorp gave Spotlight Talk at CDC Workshop on Gaussian Process Learning-Based Control
  • Date:

    December 5, 2022

  • Where:

    Cancun, Mexico

  • Description:

    Karl Berntorp was an invited speaker at the workshop on Gaussian Process Learning-Based Control organized at the Conference on Decision and Control (CDC) 2022 in Cancun, Mexico.

    The talk was part of a tutorial-style workshop aimed to provide insight into the fundamentals behind Gaussian processes for modeling and control and sketching some of the open challenges and opportunities using Gaussian processes for modeling and control. The talk titled ``Gaussian Processes for Learning and Control: Opportunities for Real-World Impact" described some of MERL's efforts in using Gaussian processes (GPs) for learning and control, with several application examples and discussing some of the key benefits and limitations with using GPs for learning-based control.

  • MERL Contact:
  • Research Areas:

    Control, Machine Learning

    •  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
      • @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}
      • }
    •  Zhan, S., Wichern, G., Laughman, C.R., Chong, A., Chakrabarty, A., "Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization", Energy and Buildings, DOI: 10.1016/​j.enbuild.2022.112278, Vol. 270, pp. 112278, September 2022.
      BibTeX TR2022-072 PDF
      • @article{Zhan2023jan,
      • author = {Zhan, Sicheng and Wichern, Gordon and Laughman, Christopher R. and Chong, Adrian and Chakrabarty, Ankush},
      • title = {Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization},
      • journal = {Energy and Buildings},
      • year = 2022,
      • volume = 270,
      • pages = 112278,
      • month = sep,
      • doi = {10.1016/j.enbuild.2022.112278},
      • url = {https://www.merl.com/publications/TR2022-072}
      • }
    •  Berntorp, K., Menner, M., "Online Constrained Bayesian Inference and Learning of Gaussian-Process State-Space Models", American Control Conference (ACC), DOI: 10.23919/​ACC53348.2022.9867635, June 2022, pp. 940-945.
      BibTeX TR2022-066 PDF
      • @inproceedings{Berntorp2022jun,
      • author = {Berntorp, Karl and Menner, Marcel},
      • title = {Online Constrained Bayesian Inference and Learning of Gaussian-Process State-Space Models},
      • booktitle = {American Control Conference (ACC)},
      • year = 2022,
      • pages = {940--945},
      • month = jun,
      • doi = {10.23919/ACC53348.2022.9867635},
      • url = {https://www.merl.com/publications/TR2022-066}
      • }
    •  Vaskov, S., Quirynen, R., Menner, M., Berntorp, K., "Friction-Adaptive Stochastic Predictive Control for Trajectory Tracking of Autonomous Vehicles", American Control Conference (ACC), DOI: 10.23919/​ACC53348.2022.9867523, June 2022, pp. 1970-1975.
      BibTeX TR2022-065 PDF
      • @inproceedings{Vaskov2022jun,
      • author = {Vaskov, Sean and Quirynen, Rien and Menner, Marcel and Berntorp, Karl},
      • title = {Friction-Adaptive Stochastic Predictive Control for Trajectory Tracking of Autonomous Vehicles},
      • booktitle = {American Control Conference (ACC)},
      • year = 2022,
      • pages = {1970--1975},
      • month = jun,
      • doi = {10.23919/ACC53348.2022.9867523},
      • url = {https://www.merl.com/publications/TR2022-065}
      • }
    •  Xu, W., Jones, C., Svetozarevic, B., Laughman, C.R., Chakrabarty, A., "VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints", American Control Conference (ACC), June 2022, pp. 5288-5293.
      BibTeX TR2022-064 PDF
      • @inproceedings{Xu2022jun,
      • author = {Xu, Wenjie and Jones, Colin and Svetozarevic, Bratislav and Laughman, Christopher R. and Chakrabarty, Ankush},
      • title = {VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints},
      • booktitle = {American Control Conference (ACC)},
      • year = 2022,
      • pages = {5288--5293},
      • month = jun,
      • isbn = {978-1-6654-5197-0},
      • url = {https://www.merl.com/publications/TR2022-064}
      • }
    •  Quirynen, R., Berntorp, K., "Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic NMPC", IFAC Conference on Nonlinear Model Predictive Control, DOI: 10.1016/​j.ifacol.2021.08.527, July 2021, pp. 76-82.
      BibTeX TR2021-084 PDF
      • @inproceedings{Quirynen2021jul,
      • author = {Quirynen, Rien and Berntorp, Karl},
      • title = {Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic NMPC},
      • booktitle = {IFAC Conference on Nonlinear Model Predictive Control},
      • year = 2021,
      • pages = {76--82},
      • month = jul,
      • doi = {10.1016/j.ifacol.2021.08.527},
      • url = {https://www.merl.com/publications/TR2021-084}
      • }
    •  Berntorp, K., "Online Bayesian Inference and Learning of Gaussian-Process State-SpaceModels", Automatica, DOI: 10.1016/​j.automatica.2021.109613, Vol. 129, March 2021.
      BibTeX TR2021-026 PDF
      • @article{Berntorp2021mar,
      • author = {Berntorp, Karl},
      • title = {Online Bayesian Inference and Learning of Gaussian-Process State-SpaceModels},
      • journal = {Automatica},
      • year = 2021,
      • volume = 129,
      • month = mar,
      • doi = {10.1016/j.automatica.2021.109613},
      • issn = {0005-1098},
      • url = {https://www.merl.com/publications/TR2021-026}
      • }