Dynamical Systems
Exploiting nonlinearity and shaping dynamics in creative and deeply mathematical ways.
We apply dynamical systems theory in applications ranging from space probe trajectory optimization to elevator suspensions. We also develop fundamental theory and computational methods in fluid dynamics.
Quick Links
-
Researchers
Stefano
Di Cairano
Yebin
Wang
Avishai
Weiss
Abraham P.
Vinod
Scott A.
Bortoff
Christopher R.
Laughman
Ankush
Chakrabarty
Saviz
Mowlavi
Hassan
Mansour
Hongtao
Qiao
Petros T.
Boufounos
Daniel N.
Nikovski
Purnanand
Elango
Chungwei
Lin
Abraham
Goldsmith
Devesh K.
Jha
Yanting
Ma
Pedro
Miraldo
Philip V.
Orlik
Arvind
Raghunathan
Diego
Romeres
Alexander
Schperberg
William S.
Yerazunis
Jianlin
Guo
Kieran
Parsons
Joshua
Rapp
Hongbo
Sun
Bingnan
Wang
Pu
(Perry)
Wang
Jinyun
Zhang
-
Awards
-
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, RoboticsBrief- 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.
- 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.
-
AWARD MERL’s Paper on Wi-Fi Sensing Earns Top 3% Paper Recognition at ICASSP 2023, Selected as a Best Student Paper Award Finalist Date: June 9, 2023
Awarded to: Cristian J. Vaca-Rubio, Pu Wang, Toshiaki Koike-Akino, Ye Wang, Petros Boufounos and Petar Popovski
MERL Contacts: Petros T. Boufounos; Toshiaki Koike-Akino; Pu (Perry) Wang; Ye Wang
Research Areas: Artificial Intelligence, Communications, Computational Sensing, Dynamical Systems, Machine Learning, Signal ProcessingBrief- A MERL Paper on Wi-Fi sensing was recognized as a Top 3% Paper among all 2709 accepted papers at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Co-authored by Cristian Vaca-Rubio and Petar Popovski from Aalborg University, Denmark, and MERL researchers Pu Wang, Toshiaki Koike-Akino, Ye Wang, and Petros Boufounos, the paper "MmWave Wi-Fi Trajectory Estimation with Continous-Time Neural Dynamic Learning" was also a Best Student Paper Award finalist.
Performed during Cristian’s stay at MERL first as a visiting Marie Skłodowska-Curie Fellow and then as a full-time intern in 2022, this work capitalizes on standards-compliant Wi-Fi signals to perform indoor localization and sensing. The paper uses a neural dynamic learning framework to address technical issues such as low sampling rate and irregular sampling intervals.
ICASSP, a flagship conference of the IEEE Signal Processing Society (SPS), was hosted on the Greek island of Rhodes from June 04 to June 10, 2023. ICASSP 2023 marked the largest ICASSP in history, boasting over 4000 participants and 6128 submitted papers, out of which 2709 were accepted.
- A MERL Paper on Wi-Fi sensing was recognized as a Top 3% Paper among all 2709 accepted papers at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Co-authored by Cristian Vaca-Rubio and Petar Popovski from Aalborg University, Denmark, and MERL researchers Pu Wang, Toshiaki Koike-Akino, Ye Wang, and Petros Boufounos, the paper "MmWave Wi-Fi Trajectory Estimation with Continous-Time Neural Dynamic Learning" was also a Best Student Paper Award finalist.
See All Awards for MERL -
-
News & Events
-
NEWS MERL contributes to ICRA 2025 Date: May 19, 2025 - May 23, 2025
Where: IEEE ICRA
MERL Contacts: Stefano Di Cairano; Jianlin Guo; Chiori Hori; Siddarth Jain; Devesh K. Jha; Toshiaki Koike-Akino; Philip V. Orlik; Arvind Raghunathan; Diego Romeres; Yuki Shirai; Abraham P. Vinod; Yebin Wang
Research Areas: Artificial Intelligence, Computer Vision, Control, Dynamical Systems, Machine Learning, Optimization, Robotics, Human-Computer InteractionBrief- MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2025, which was held in Atlanta, Georgia, USA, from May 19th to May 23rd.
MERL was a Bronze sponsor of the conference, and MERL researchers chaired four sessions in the areas of Manipulation Planning, Human-Robot Collaboration, Diffusion Policy, and Learning for Robot Control.
MERL researchers presented four papers in the main conference on the topics of contact-implicit trajectory optimization, proactive robotic assistance in human-robot collaboration, diffusion policy with human preferences, and dynamic and model learning of robotic manipulators. In addition, five more papers were presented in the workshops: “Structured Learning for Efficient, Reliable, and Transparent Robots,” “Safely Leveraging Vision-Language Foundation Models in Robotics: Challenges and Opportunities,” “Long-term Human Motion Prediction,” and “The Future of Intelligent Manufacturing: From Innovation to Implementation.”
MERL researcher Diego Romeres delivered an invited talk titled “Dexterous Robotics: From Multimodal Sensing to Real-World Physical Interactions.”
MERL also collaborated with the University of Padua on one of the conference’s challenges: the “3rd AI Olympics with RealAIGym” (https://ai-olympics.dfki-bremen.de).
During the conference, MERL researchers received the IEEE Transactions on Automation Science and Engineering Best New Application Paper Award for their paper titled “Smart Actuation for End-Edge Industrial Control Systems.”
About ICRA
The IEEE International Conference on Robotics and Automation (ICRA) is the flagship conference of the IEEE Robotics and Automation Society and the world’s largest and most comprehensive technical conference focused on research advances and the latest technological developments in robotics. The event attracts over 7,000 participants, 143 partners and exhibitors, and receives more than 4,000 paper submissions.
- MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2025, which was held in Atlanta, Georgia, USA, from May 19th to May 23rd.
-
NEWS MERL researchers present 7 papers at CDC 2024 Date: December 16, 2024 - December 19, 2024
Where: Milan, Italy
MERL Contacts: Ankush Chakrabarty; Vedang M. Deshpande; Stefano Di Cairano; Abraham P. Vinod; Avishai Weiss; Gordon Wichern
Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, RoboticsBrief- MERL researchers presented 7 papers at the recently concluded Conference on Decision and Control (CDC) 2024 in Milan, Italy. The papers covered a wide range of topics including safety shielding for stochastic model predictive control, reinforcement learning using expert observations, physics-constrained meta learning for positioning, variational-Bayes Kalman filtering, Bayesian measurement masks for GNSS positioning, divert-feasible lunar landing, and centering and stochastic control using constrained zonotopes.
As a sponsor of the conference, MERL maintained a booth for open discussions with researchers and students, and hosted a special session to discuss highlights of MERL research and work philosophy.
In addition, Ankush Chakrabarty (Principal Research Scientist, Multiphysical Systems Team) was an invited speaker in the pre-conference Workshop on "Learning Dynamics From Data" where he gave a talk on few-shot meta-learning for black-box identification using data from similar systems.
- MERL researchers presented 7 papers at the recently concluded Conference on Decision and Control (CDC) 2024 in Milan, Italy. The papers covered a wide range of topics including safety shielding for stochastic model predictive control, reinforcement learning using expert observations, physics-constrained meta learning for positioning, variational-Bayes Kalman filtering, Bayesian measurement masks for GNSS positioning, divert-feasible lunar landing, and centering and stochastic control using constrained zonotopes.
See All News & Events for Dynamical Systems -
-
Internships
-
ST0105: Internship - Surrogate Modeling for Sound Propagation
MERL is seeking a motivated and qualified individual to work on fast surrogate models for sound emission and propagation from complex vibrating structures, with applications in HVAC noise reduction. The ideal candidate will be a PhD student in engineering or related fields with a solid background in frequency-domain acoustic modeling and numerical techniques for partial differential equations (PDEs). Preferred skills include knowledge of the boundary element method (BEM), data-driven modeling, and physics-informed machine learning. Publication of the results obtained during the internship is expected. The duration is expected to be at least 3 months with a flexible start date.
-
CA0148: Internship - Motion Planning and Control for Autonomous Articulated Vehicles
MERL is seeking an outstanding intern to collaborate in the development of motion planning and control for autonomous articulated vehicles. The ideal candidate is expected to be working towards a PhD in electrical, mechanical, aerospace engineering, robotics, control or related areas, with a strong emphasis on motion planning and control, possibly with applications to ground vehicles, to have experience in at least some of path/motion planning algorithms (A*, D*, graph-search) and optimization-based control (e.g., model predictive control), to have excellent coding skills in MATLAB/Simulink and a strong publication record. The expected start date is the Spring/Early Summer 2025 and the expected duration is 6-9 months, depending on candidate availability and interests.
Required Specific Experience
- Path/motion planning algorithms (A*, D*, graph-search)
- Nonlinear model predictive control
- Programming in Matlab/Simulink
- Applications to mobile robots or vehicles
Additional Useful Experience
- Nonlinear MPC Design in CasADi
- Code generation tools and dSPACE
- Applications to autonomous vehicles and articulated vehicles
-
CA0153: Internship - High-Fidelity Visualization and Simulation for Space Applications
MERL is seeking a highly motivated graduate student to develop high-fidelity full-stack GNC simulators for space applications. The ideal candidate has strong experience with rendering engines, synthetic image generation, and computer vision, as well as familiarity with spacecraft dynamics, motion planning, and state estimation. The developed software should allow for closed-loop execution with the synthetic imagery, and ideally allow for real-time visualization. Publication of results produced during the internship is desired. The expected duration of the internship is 3-6 months with a flexible start date.
Required Specific Experience
- Current enrollment in a graduate program in Aerospace, Computer Science, Robotics, Mechanical, Electrical Engineering, or a related field
-
Experience with one or more of Blender, Unreal, Unity, along with their APIs
-
Strong programming skills in one or more of Matlab, Python, and/or C/C++
See All Internships for Dynamical Systems -
-
Openings
See All Openings at MERL -
Recent Publications
- , "Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning", IEEE International Conference on Robotics and Automation (ICRA), May 2025.BibTeX TR2025-065 PDF
- @inproceedings{Giammarino2025may,
- author = {Giammarino, Vittorio and Queeney, James and Paschalidis, Ioannis Ch.},
- title = {{Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning}},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2025,
- month = may,
- url = {https://www.merl.com/publications/TR2025-065}
- }
- , "Simultaneous Collision Detection and Force Estimation for Dynamic Quadrupedal Locomotion", IEEE International Conference on Robotics and Automation (ICRA), May 2025.BibTeX TR2025-063 PDF
- @inproceedings{Zhou2025may,
- author = {Zhou, Ziyi and {Di Cairano}, Stefano and Wang, Yebin and Berntorp, Karl},
- title = {{Simultaneous Collision Detection and Force Estimation for Dynamic Quadrupedal Locomotion}},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2025,
- month = may,
- url = {https://www.merl.com/publications/TR2025-063}
- }
- , "Time-optimal single-scalar control on a qubit of unitary dynamics", Physical Review, April 2025.BibTeX TR2025-048 PDF
- @article{Lin2025apr2,
- author = {Lin, Chungwei and Boufounos, Petros T. and Ma, Yanting and Wang, Yebin and Ding, Qi and Sels, Dries and Chien, Chih-Chun},
- title = {{Time-optimal single-scalar control on a qubit of unitary dynamics}},
- journal = {Physical Review},
- year = 2025,
- month = apr,
- url = {https://www.merl.com/publications/TR2025-048}
- }
- , "Projection-free computation of robust controllable sets with constrained zonotopes", Automatica, DOI: 10.1016/j.automatica.2025.112211, Vol. 175, pp. 112211, March 2025.BibTeX TR2025-023 PDF Video
- @article{Vinod2025mar,
- author = {Vinod, Abraham P. and Weiss, Avishai and Di Cairano, Stefano},
- title = {{Projection-free computation of robust controllable sets with constrained zonotopes}},
- journal = {Automatica},
- year = 2025,
- volume = 175,
- pages = 112211,
- month = mar,
- doi = {10.1016/j.automatica.2025.112211},
- issn = {0005-1098},
- url = {https://www.merl.com/publications/TR2025-023}
- }
- , "PIETRA: Physics-Informed Evidential Learning for Traversing Out-of-Distribution Terrain", IEEE Robotics and Automation Letters (RA-L), DOI: 10.1109/LRA.2025.3527285, Vol. 10, No. 3, pp. 2359-2366, February 2025.BibTeX TR2025-022 PDF
- @article{Cai2025feb,
- author = {Cai, Xiaoyi and Queeney, James and Xu, Tong and Datar, Aniket and Pan, Chenhui and Miller, Max and Flather, Ashton and Osteen, Philip R. and Roy, Nicholas and Xiao, Xuesu and How, Jonathan P.},
- title = {{PIETRA: Physics-Informed Evidential Learning for Traversing Out-of-Distribution Terrain}},
- journal = {IEEE Robotics and Automation Letters (RA-L)},
- year = 2025,
- volume = 10,
- number = 3,
- pages = {2359--2366},
- month = feb,
- doi = {10.1109/LRA.2025.3527285},
- url = {https://www.merl.com/publications/TR2025-022}
- }
- , "Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse", IEEE Transactions on Automatic Control, DOI: 10.1109/TAC.2024.3454011, Vol. 70, No. 2, pp. 1236-1243, February 2025.BibTeX TR2025-015 PDF
- @article{Queeney2025feb,
- author = {Queeney, James and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
- title = {{Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse}},
- journal = {IEEE Transactions on Automatic Control},
- year = 2025,
- volume = 70,
- number = 2,
- pages = {1236--1243},
- month = feb,
- doi = {10.1109/TAC.2024.3454011},
- url = {https://www.merl.com/publications/TR2025-015}
- }
- , "Decentralized, Safe, Multi-agent Motion Planning for Drones Under Uncertainty via Filtered Reinforcement Learning", IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2024.3433229, Vol. 32, No. 6, pp. 2492-2499, January 2025.BibTeX TR2024-136 PDF
- @article{Vinod2025jan,
- author = {Vinod, Abraham P. and Safaoui, Sleiman and Summers, Tyler and Yoshikawa, Nobuyuki and {Di Cairano}, Stefano},
- title = {{Decentralized, Safe, Multi-agent Motion Planning for Drones Under Uncertainty via Filtered Reinforcement Learning}},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2025,
- volume = 32,
- number = 6,
- pages = {2492--2499},
- month = jan,
- doi = {10.1109/TCST.2024.3433229},
- url = {https://www.merl.com/publications/TR2024-136}
- }
- , "Invariant Set Planning for Quadrotors: Design, Analysis, Experiments", IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2024.3492813, Vol. 33, No. 2, pp. 449-462, January 2025.BibTeX TR2025-010 PDF
- @article{Greiff2025jan,
- author = {Greiff, Marcus and Sinhmar, Himani and Weiss, Avishai and Berntorp, Karl and {Di Cairano}, Stefano},
- title = {{Invariant Set Planning for Quadrotors: Design, Analysis, Experiments}},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2025,
- volume = 33,
- number = 2,
- pages = {449--462},
- month = jan,
- doi = {10.1109/TCST.2024.3492813},
- issn = {1063-6536},
- url = {https://www.merl.com/publications/TR2025-010}
- }
- , "Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning", IEEE International Conference on Robotics and Automation (ICRA), May 2025.
-
Videos
-
Software & Data Downloads
