- Date: July 12, 2021
Research Areas: Control, Dynamical Systems, Optimization
Brief - MERL researcher Rien Quirynen will present work in collaboration with Karl Berntorp on "Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic Nonlinear MPC" as a keynote speaker at the 7th IFAC Conference on Nonlinear Model Predictive Control 2021 on July, 12th. The paper is 1 out of 5 keynote presentations chosen among more than 50 accepted papers at the conference. An abstract of the talk can be found in the link below.
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- Date: April 22, 2021
Where: Houston, Texas
Research Areas: Control, Dynamical Systems, Robotics, Signal Processing
Brief - The invited seminar "System Design, Planning, and Control for Autonomous Driving" was part of the Distinguished Seminar series at the Department of Mechanical Engineering at the University of Houston, Houston, Tx. The invited lecture described MERL research related to the different system components involved in autonomous driving, with particular focus on motion-planning and predictive-control methods.
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- Date: April 9, 2021
MERL Contact: Ankush Chakrabarty
Research Areas: Control, Machine Learning, Multi-Physical Modeling, Optimization
Brief - Ankush Chakrabarty, a Research Scientist at MERL's Multiphysical Systems (MS) Team, gave an invited talk on "Learning for Control and Estimation using Digital Twins" at the Department of Electrical and Computer Engineering Seminar Series organized at UIC. The talk proposed new learning-based control/estimation architectures that can utilize simulation data obtained from digital twins to add self-optimization and constraint-enforcement features to grey/black-box control systems.
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- Date: April 6, 2021
Where: Linköping University, Sweden
Research Areas: Control, Dynamical Systems, Robotics
Brief - MERL researcher Karl Berntorp was invited to give a lecture in the ELLIIT PhD course "Motion Planning and Control" at the Division of Vehicular Systems, Department of Electrical Engineering, Linköping University. The course is open for Ph.D. students as well as senior undergraduate students, and covers both fundamental algorithms and state-of-the-art methods for motion planning and control. The invited lecture described MERL research on the use of invariant sets for safe motion planning and control, with application to autonomous vehicles.
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- Date: March 7, 2021
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Robotics
Brief - Stefano Di Cairano has joined the Editorial Board of the IEEE Transactions on Intelligent Vehicles (T-IV) as an Associate Editor. The IEEE T-IV publishes peer-reviewed articles in the area of intelligent vehicles in a roadway environment, and in particular in automated vehicles. While primarily led by the IEEE ITS Society, IEEE T-IV is an IEEE multi-society journal.
As Associate Editor Stefano will be responsible for the review process of some of the papers submitted to T-IV and will work with the Editorial Board to monitor the status and continuously strengthen the journal.
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- Date & Time: Wednesday, December 9, 2020; 1:00-5:00PM EST
Location: Virtual
MERL Contacts: Elizabeth Phillips; Anthony Vetro
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
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- Date: October 8, 2020
Where: Linkoping University
Research Areas: Control, Dynamical Systems, Robotics, Signal Processing
Brief - MERL researcher Karl Berntorp was invited to give a lecture in the class "Autonomous vehicles – planning, control, and learning systems" at the Division of Vehicular Systems, Department of Electrical Engineering, Linkoping University. The course is for the engineering-program students at Linkoping University and gives a basic understanding of the available models, methods, and software libraries to work on autonomous vehicles, with particular focus on motion-planning and control methods. The invited lecture described the different system components and design of motion planning and predictive control methods targeted to autonomous driving.
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- Date: August 26, 2020
Awarded to: Marcus Greiff, Anders Robertsson, Karl Berntorp
Research Areas: Control, Signal Processing
Brief - Marcus Greiff, a former MERL intern from the Department of Automatic Control, Lund University, Sweden, won one of three 2020 CCTA Outstanding Student Paper Awards and the Best Student Paper Award at the 2020 IEEE Conference on Control Technology and Applications. The research leading up to the awarded paper titled 'MSE-Optimal Measurement Dimension Reduction in Gaussian Filtering', concerned how to select a reduced set of measurements in estimation applications while minimally degrading performance, was done in collaboration with Karl Berntorp at MERL.
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- Date: August 25, 2020
MERL Contact: Ankush Chakrabarty
Research Areas: Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics
Brief - Ankush Chakrabarty co-organized an invited session on “Data-Driven Control For Industrial Applications” at the IEEE Conference on Control Technology and Applications with Shahin Shahrampour (Asst. Prof., Texas A&M). Talks covered topics including reinforcement learning for aerospace systems, constrained reinforcement learning for motors, deep Q learning for traffic systems and participants included speakers from Stanford University, North Carolina State University, Texas A&M, Oklahoma State University, University of Science and Technology at Beijing, and TU Delft.
MERL presented research (Chakrabarty, Danielson, Wang) on constraint-enforcing output-tracking with approximate dynamic programming for servomotor systems.
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- Date: August 3, 2020
Where: Cambridge, MA
MERL Contact: Abraham P. Vinod
Research Areas: Artificial Intelligence, Control, Optimization, Robotics
Brief - Mitsubishi Electric Research Laboratories is excited to welcome Abraham P. Vinod as the newest member of its research staff, in the Control for Autonomy Team. Abraham joins MERL from the University of Texas, Austin, where he was a Postdoctoral Research Fellow. He obtained his Ph.D. from the University of New Mexico. His PhD research produced scalable algorithms for providing safety guarantees for stochastic, control-constrained, dynamical systems, with applications to motion planning. In his postdoctoral research, Abraham studied theory and algorithms for on-the-fly, data-driven control of unknown systems under severely limited data. His current research interests lie in the intersection of optimization, control, and learning. Abraham won the Best Student Paper Award at the 2017 ACM Hybrid Systems: Computation and Control Conference, was a finalist for the Best Paper Award in the 2018 ACM Hybrid Systems: Computation and Control Conference, and won the best undergraduate student research project award at the Indian Institute of Technology, Madras.
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- Date: July 1, 2020 - July 3, 2020
Where: Denver, Colorado (virtual)
MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, Optimization
Brief - At the American Control Conference, MERL presented 10 papers on subjects including autonomous-vehicle decision making and motion planning, nonlinear estimation for thermal-fluid models and GNSS positioning, learning-based reference governors and reference governors for railway vehicles, and fail-safe rendezvous control.
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- Date: July 7, 2021 - July 14, 2021
Where: Bratislava, Slovakia
MERL Contact: Stefano Di Cairano
Research Areas: Control, Machine Learning, Optimization
Brief - MERL researcher Stefano Di Cairano has been appointed as Vice-Chair for Industry of the International Program Committee of the 7th IFAC Symposium on Nonlinear Model Predictive Control, which will be held in Bratislava, Slovakia, in July 2021.
IFAC NMPC is the main symposium focused on model predictive control, theory, methods and applications, includes contributions on control, optimization, and machine learning research, and is held every 3 years.
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- Date: December 8, 2020 - December 11, 2020
Where: IEEE Conference on Decision and Control (CDC)
MERL Contact: Ankush Chakrabarty
Research Areas: Control, Optimization
Brief - Ankush Chakrabarty, a Research Scientist in MERL's Multi-Physical Systems, will be serving as an Associate Editor at the 2020 IEEE Conference on Decision and Control (CDC).
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- Date: February 10, 2020
Research Areas: Control, Data Analytics, Dynamical Systems
Brief - Dr. Benosman has been nominated as an associate editor at the IEEE Control Systems Letters (L-CSS).
The L-CSS publishes peer-reviewed brief articles that provide a rapid and concise account of innovative ideas regarding the theory, design, and applications of all aspects of control engineering.
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- Date: December 12, 2019
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Robotics
Brief - Stefano Di Cairano has been appointed inaugural chair of the IEEE CSS Technology Conference Editorial Board. In this role Stefano will coordinate the creation and maintenance of the Editorial Board, and will coordinate the editorial board activities supporting the IEEE CCTA conference series, including manuscript assignment to associate editors, monitoring of the manuscript assessment, and program finalization with the conference program chairs. Stefano will also work with the other IEEE CSS Editorial Board Chairs and IEEE CSS Leadership to ensure the quality and improve the processes of IEEE CSS publications.
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- Date: December 11, 2019 - December 13, 2019
Where: Nice, France
MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano
Research Areas: Control, Machine Learning, Optimization
Brief - At the Conference on Decision and Control, MERL presented 8 papers on subjects including estimation for thermal-fluid models and transportation networks, analysis of HVAC systems, extremum seeking for multi-agent systems, reinforcement learning for vehicle platoons, and learning with applications to autonomous vehicles.
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- Date: October 10, 2019
Awarded to: Devesh Jha, Nurali Virani, Zhenyuan Yuan, Ishana Shekhawat and Asok Ray
MERL Contact: Devesh K. Jha
Research Areas: Artificial Intelligence, Control, Data Analytics, Machine Learning, Robotics
Brief - MERL researcher Devesh Jha has won the Rudolf Kalman Best Paper Award 2019 for the paper entitled "Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models". This paper, published in a Special Commemorative Issue for Rudolf E. Kalman in the ASME JDSMC in March 2018, uses Bayesian filtering for imitation learning in Hidden Mode Hybrid Systems. This award is given annually by the Dynamic Systems and Control Division of ASME to the authors of the best paper published in the ASME Journal of Dynamic Systems Measurement and Control during the preceding year.
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- Date: September 25, 2019
Where: Rensselaer Polytechnic Institute (RPI), Troy, NY
MERL Contact: Scott A. Bortoff
Research Areas: Control, Multi-Physical Modeling
Brief - The seminar, entitled “HVAC System Control and Optimization,” was part of the Mercer Distinguished Lecture Series in the Electrical, Computer and Systems Engineering Department at Rensselaer Polytechnic Institute (RPI), Troy, NY. Given on Wednesday September 25, 2019, it focused on the systems engineering and control issues associated with highly integrated Heating, Ventilation and Air Conditioning Systems for low and zero energy buildings.
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- Date: August 19, 2019 - August 23, 2019
Where: AI for Engineering Summer School 2019
MERL Contact: Ankush Chakrabarty
Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning
Brief - Ankush Chakrabarty, a Visiting Research Scientist in MERL's Control and Dynamical Systems group, gave an invited talk at the AI for Engineering Summer School 2019 hosted by Autodesk. The talk briefly described MERL's research areas, and focused on Dr. Chakrabarty's work at MERL (with collaborators from the CD and DA group) on the use of supervised learning for verification of control systems with simulators/neural nets in the loop, and on constraint-enforcing reinforcement learning. Other speakers at the event included researchers from various academic and industrial research facilities including U Toronto, UW-Seattle, Carnegie Mellon U, the Vector Institute, and the Montreal Institute for Learning Algorithms.
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- Date: July 10, 2019 - July 12, 2019
Where: Philadelphia
MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, Optimization
Brief - At the American Control Conference, MERL presented 8 papers on subjects including model predictive control applications, estimation and motion planning for vehicles, modular control architectures, and adaptation and learning.
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- Date: June 25, 2019 - June 28, 2019
Where: Naples, Italy
MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Christopher R. Laughman; Daniel N. Nikovski; Diego Romeres; William S. Yerazunis
Research Areas: Control, Machine Learning, Optimization
Brief - The European Control Conference is the premier control conference in Europe. This year MERL was well represented with papers on control for HVAC, machine learning for estimation and control, robot assembly, and optimization methods for control.
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- Date: June 10, 2019 - June 14, 2019
Where: Paris
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Optimization
Brief - MERL researcher Stefano Di Cairano and Prof. Ilya Kolmanovsky, Dept. Aerospace Engineering, the University of Michigan, were invited to teach a class on "Predictive and Optimization Based Control for Automotive and Aerospace Application" at the 2019 International Graduate School in Control, of the European Embedded Control Institute (EECI). Every year EECI invites world renown experts to teach 21-hours class modules, mostly for PhD students but also for professionals, on selected control subjects. Stefano and Ilya's class was attended by 30 "students" from both academia and industry, from all around the world, interested in automotive and aerospace control. The module described the fundamentals of modeling and control design in automotive and aerospace through lectures, real world examples and exercises, and placed particular emphasis on techniques such as MPC, reference governors, and optimal control.
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- Date & Time: July 29, 2019; 10 AM
Where: US National Congress on Computational Mechanics 2019, in Austin Texas
Research Areas: Control, Data Analytics, Dynamical Systems
Brief - MERL researcher Mouhacine Benosman will present his work on 'Learning-based Robust Stabilization for Reduced-Order Models of 3D Boussinesq Equations' as a keynote speaker at the mini-symposium 'Data assimilation in Model Order Techniques for Computational Mechanics', during the next US National Congress on Computational Mechanics 2019, in Austin Texas.
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- Date: April 15, 2019
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - Stefano Di Cairano, senior team leader and distinguished research scientist in the Control and Dynamical Systems group, was interviewed in the April 2019 issue of IEEE Control Systems Magazine. Stefano described himself, promising opportunities in the control field, and how his passion for control research fits well into the industrial research laboratory setting at MERL. It is very good reading for any young researcher considering possible career trajectories.
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- Date: April 28, 2019
Where: 3rd IAVSD Workshop on Dynamics of Road Vehicles: Connected and Automated Vehicles
MERL Contact: Stefano Di Cairano
Research Areas: Control, Optimization, Robotics
Brief - Stefano Di Cairano, Distinguished Scientist and Senior Team Leader in the Control and Dynamical Systems Group, will give an invited talk entitled: "Modularity, integration and synergy in architectures for autonomous driving" that covers recent work in the lab concerning building a modular, robust control framework for autonomous driving.
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