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.
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Researchers
Stefano
Di Cairano
Karl
Berntorp
Mouhacine
Benosman
Yebin
Wang
Avishai
Weiss
Scott A.
Bortoff
Abraham P.
Vinod
Christopher R.
Laughman
Ankush
Chakrabarty
Hongtao
Qiao
Saviz
Mowlavi
Hassan
Mansour
Daniel N.
Nikovski
Chungwei
Lin
Petros T.
Boufounos
Abraham
Goldsmith
Devesh K.
Jha
Pedro
Miraldo
Philip V.
Orlik
James
Queeney
Diego
Romeres
Jianlin
Guo
Yanting
Ma
Kieran
Parsons
Arvind
Raghunathan
Hongbo
Sun
Bingnan
Wang
Pu
(Perry)
WangWilliam S.
Yerazunis
Jinyun
Zhang
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Awards
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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.
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News & Events
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NEWS MERL researchers present 9 papers at ACC 2024 Date: July 10, 2024 - July 12, 2024
Where: Toronto, Canada
MERL Contacts: Karl Berntorp; Ankush Chakrabarty; Vedang M. Deshpande; Stefano Di Cairano; Christopher R. Laughman; Arvind Raghunathan; Abraham P. Vinod; Yebin Wang; Avishai Weiss
Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, RoboticsBrief- MERL researchers presented 9 papers at the recently concluded American Control Conference (ACC) 2024 in Toronto, Canada. The papers covered a wide range of topics including data-driven spatial monitoring using heterogenous robots, aircraft approach management near airports, computation fluid dynamics-based motion planning for drones facing winds, trajectory planning for coordinated monitoring using a team of drones and a ground carrier vehicle, ensemble Kalman smoothing-based model predictive control for motion planning for autonomous vehicles, system identification for Lithium-ion batteries, physics-constrained deep Kalman filters for vapor compression systems, switched reference governors for constrained systems, and distributed road-map monitoring using onboard sensors.
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, Abraham Vinod served as a panelist at the Student Networking Event at the conference. The student networking event provides an opportunity for all interested students to network with professionals working in industry, academia, and national laboratories during a structured event, and encourages their continued participation as the future leaders in the field.
- MERL researchers presented 9 papers at the recently concluded American Control Conference (ACC) 2024 in Toronto, Canada. The papers covered a wide range of topics including data-driven spatial monitoring using heterogenous robots, aircraft approach management near airports, computation fluid dynamics-based motion planning for drones facing winds, trajectory planning for coordinated monitoring using a team of drones and a ground carrier vehicle, ensemble Kalman smoothing-based model predictive control for motion planning for autonomous vehicles, system identification for Lithium-ion batteries, physics-constrained deep Kalman filters for vapor compression systems, switched reference governors for constrained systems, and distributed road-map monitoring using onboard sensors.
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NEWS Diego Romeres gave an invited talk at the Padua University's Seminar series on "AI in Action" Date: April 9, 2024
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Dynamical Systems, Machine Learning, Optimization, RoboticsBrief- Diego Romeres, Principal Research Scientist and Team Leader in the Optimization and Robotics Team, was invited to speak as a guest lecturer in the seminar series on "AI in Action" in the Department of Management and Engineering, at the University of Padua.
The talk, entitled "Machine Learning for Robotics and Automation" described MERL's recent research on machine learning and model-based reinforcement learning applied to robotics and automation.
- Diego Romeres, Principal Research Scientist and Team Leader in the Optimization and Robotics Team, was invited to speak as a guest lecturer in the seminar series on "AI in Action" in the Department of Management and Engineering, at the University of Padua.
See All News & Events for Dynamical Systems -
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Internships
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CA2132: Optimization Algorithms for Motion Planning and Predictive Control
MERL is looking for a highly motivated and qualified individual to work on tailored computational algorithms for optimization-based motion planning and predictive control applications in autonomous systems (vehicles, mobile robots). The ideal candidate should have experience in either one or multiple of the following topics: convex and non-convex optimization, stochastic predictive control (e.g., scenario trees), interaction-aware motion planning, machine learning, learning-based model predictive control, mathematical programs with complementarity constraints (MPCCs), optimal control, and real-time optimization. PhD students in engineering or mathematics, especially with a focus on research related to any of the above topics are encouraged to apply. Publication of relevant results in conference proceedings or journals is expected. Capability of implementing the designs and algorithms in MATLAB/Python is required; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is 3 months, and the start date is flexible.
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ST2083: Deep Learning for Radar Perception
The Computation Sensing team at MERL is seeking a highly motivated intern to conduct fundamental research in radar perception. Expertise in deep learning-based object detection, multiple object tracking, data association, and representation learning (detection points, heatmaps, and raw radar waveforms) is required. Previous hands-on experience on open indoor/outdoor radar datasets is a plus. Familiarity with the concept of FMCW, MIMO, and range-Doppler-angle spectrum is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments with MERL in-house testbed, and prepare results for patents and publication. The expected duration of the internship is 3 months with a flexible start date.
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CA2131: Collaborative Legged Robots
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on control and planning algorithms for legged robots for support activities of and collaboration with humans. The ideal candidate is expected to be working towards a PhD with strong emphasis in robotics control and planning and to have interest and background in as many as possible of: motion planning algorithms, control for legged robot locomotions, legged robots, perception and sensing with multiple sensors, SLAM, vision-based control. Good programming skills in Python or C/C++ are required. The expected start of of the internship is flexible, with duration of 3--6 months.
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Recent Publications
- "Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning", IEEE Transactions on Robotics, DOI: 10.1109/TRO.2024.3387010, Vol. 40, pp. 2529-2542, July 2024.BibTeX TR2024-048 PDF Video
- @article{Safaoui2024jul,
- author = {Safaoui, Sleiman and Vinod, Abraham P. and Chakrabarty, Ankush and Quirynen, Rien and Yoshikawa, Nobuyuki and Di Cairano, Stefano},
- title = {Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning},
- journal = {IEEE Transactions on Robotics},
- year = 2024,
- volume = 40,
- pages = {2529--2542},
- month = jul,
- doi = {10.1109/TRO.2024.3387010},
- url = {https://www.merl.com/publications/TR2024-048}
- }
, - "Leveraging Computational Fluid Dynamics in UAV Motion Planning", American Control Conference (ACC), July 2024.BibTeX TR2024-050 PDF Video
- @inproceedings{Huang2024jul,
- author = {Huang, Yunshen and Greiff, Marcus and Vinod, Abraham P. and Di Cairano, Stefano}},
- title = {Leveraging Computational Fluid Dynamics in UAV Motion Planning},
- booktitle = {American Control Conference (ACC)},
- year = 2024,
- month = jul,
- url = {https://www.merl.com/publications/TR2024-050}
- }
, - "Decoupled Trajectory Planning for Monitoring UAVs and UGV Carrier by Reachable Sets", American Control Conference (ACC), July 2024.BibTeX TR2024-092 PDF
- @inproceedings{Kim2024jul,
- author = {Kim, Taewan and Vinod, Abraham P. and Di Cairano, Stefano}},
- title = {Decoupled Trajectory Planning for Monitoring UAVs and UGV Carrier by Reachable Sets},
- booktitle = {American Control Conference (ACC)},
- year = 2024,
- month = jul,
- url = {https://www.merl.com/publications/TR2024-092}
- }
, - "A Switched Reference Governor for High Performance Trajectory Tracking under State and Input Constraints", American Control Conference (ACC), July 2024.BibTeX TR2024-091 PDF
- @inproceedings{Wang2024jul,
- author = {Wang, Nan and Di Cairano, Stefano and Sanfelice, Ricardo}},
- title = {A Switched Reference Governor for High Performance Trajectory Tracking under State and Input Constraints},
- booktitle = {American Control Conference (ACC)},
- year = 2024,
- month = jul,
- url = {https://www.merl.com/publications/TR2024-091}
- }
, - "Distributed Road-Map Monitoring Using Onboard Sensors", American Control Conference (ACC), July 2024.BibTeX TR2024-093 PDF
- @inproceedings{Zhang2024jul,
- author = {Zhang, Yanyu and Greiff, Marcus and Ren, Wei and Berntorp, Karl}},
- title = {Distributed Road-Map Monitoring Using Onboard Sensors},
- booktitle = {American Control Conference (ACC)},
- year = 2024,
- month = jul,
- url = {https://www.merl.com/publications/TR2024-093}
- }
, - "Parametrized Maneuvers Governor for Decision Making in Automated Driving" in Nonlinear and Constrained Control - Applications, Synergies, Challenges and Opportunities., June 2024.BibTeX TR2024-086 PDF
- @incollection{DiCairano2024jun,
- author = {Di Cairano, Stefano and Skibik, Terrence and Vinod, Abraham P. and Weiss, Avishai and Berntorp, Karl and Okura, Yuichi}},
- title = {Parametrized Maneuvers Governor for Decision Making in Automated Driving},
- booktitle = {Nonlinear and Constrained Control - Applications, Synergies, Challenges and Opportunities.},
- year = 2024,
- month = jun,
- url = {https://www.merl.com/publications/TR2024-086}
- }
, - "Variational Bayes Kalman Filter for Joint Vehicle Localization and Road Mapping Using Onboard Sensors", European Control Conference (ECC), June 2024.BibTeX TR2024-082 PDF
- @inproceedings{Berntorp2024jun,
- author = {Berntorp, Karl and Greiff, Marcus}},
- title = {Variational Bayes Kalman Filter for Joint Vehicle Localization and Road Mapping Using Onboard Sensors},
- booktitle = {European Control Conference (ECC)},
- year = 2024,
- month = jun,
- url = {https://www.merl.com/publications/TR2024-082}
- }
, - "A Robust Invariant Set Planner For Quadrotors", European Control Conference (ECC), June 2024.BibTeX TR2024-081 PDF
- @inproceedings{Greiff2024jun,
- author = {Greiff, Marcus and Weiss, Avishai and Berntorp, Karl and Di Cairano, Stefano}},
- title = {A Robust Invariant Set Planner For Quadrotors},
- booktitle = {European Control Conference (ECC)},
- year = 2024,
- month = jun,
- url = {https://www.merl.com/publications/TR2024-081}
- }
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- "Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning", IEEE Transactions on Robotics, DOI: 10.1109/TRO.2024.3387010, Vol. 40, pp. 2529-2542, July 2024.
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Videos