Optimization
Efficient solutions to large-scale problems.
Much of MERL's research activity involves formulating scientific and engineering problems as optimizations, which can be solved in an efficient way. We have developed fundamental algorithms to better solve classic problems, such as quadratic programs and minimum-cost paths. Our work also involves developing theoretical bounds to understand performance limits.
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Researchers
Stefano
Di Cairano
Toshiaki
Koike-Akino
Ankush
Chakrabarty
Daniel N.
Nikovski
Arvind
Raghunathan
Christopher R.
Laughman
Philip V.
Orlik
Mouhacine
Benosman
Karl
Berntorp
Yebin
Wang
Ye
Wang
Kieran
Parsons
Devesh K.
Jha
Matthew
Brand
Scott A.
Bortoff
Petros T.
Boufounos
Hassan
Mansour
Abraham P.
Vinod
Diego
Romeres
Pu
(Perry)
Wang
Jianlin
Guo
Avishai
Weiss
Dehong
Liu
Hongbo
Sun
Vedang M.
Deshpande
Hongtao
Qiao
Yanting
Ma
Saviz
Mowlavi
Yuki
Shirai
Bingnan
Wang
Gordon
Wichern
William S.
Yerazunis
Jinyun
Zhang
Purnanand
Elango
Abraham
Goldsmith
Chungwei
Lin
Wataru
Tsujita
Jose
Amaya
Anoop
Cherian
Radu
Corcodel
Pedro
Miraldo
Joshua
Rapp
Alexander
Schperberg
Na
Li
Jing
Liu
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Awards
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AWARD MERL Researchers Win Best Workshop Poster Award at the 2023 IEEE International Conference on Robotics and Automation (ICRA) Date: June 2, 2023
Awarded to: Yuki Shirai, Devesh Jha, Arvind Raghunathan and Dennis Hong
MERL Contacts: Devesh K. Jha; Arvind Raghunathan
Research Areas: Artificial Intelligence, Optimization, RoboticsBrief- MERL's paper titled: "Closed-Loop Tactile Controller for Tool Manipulation" Won the Best Poster Award in the workshop on "Embracing contacts : Making robots physically interact with our world". First author and MERL intern, Yuki Shirai, was presented with the award at a ceremony held at ICRA in London. MERL researchers Devesh Jha, Principal Research Scientist, and Arvind Raghunathan, Senior Principal Research Scientist and Senior Team Leader as well as Prof. Dennis Hong of University of California, Los Angeles are also coauthors.
The paper presents a technique to manipulate an object using a tool in a closed-loop fashion using vision-based tactile sensors. More information about the workshop and the various speakers can be found here https://sites.google.com/view/icra2023embracingcontacts/home.
- MERL's paper titled: "Closed-Loop Tactile Controller for Tool Manipulation" Won the Best Poster Award in the workshop on "Embracing contacts : Making robots physically interact with our world". First author and MERL intern, Yuki Shirai, was presented with the award at a ceremony held at ICRA in London. MERL researchers Devesh Jha, Principal Research Scientist, and Arvind Raghunathan, Senior Principal Research Scientist and Senior Team Leader as well as Prof. Dennis Hong of University of California, Los Angeles are also coauthors.
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AWARD Arvind Raghunathan receives Roberto Tempo Best CDC Paper Award at 2022 IEEE Conference on Decision & Control (CDC) Date: December 8, 2022
Awarded to: Arvind Raghunathan
MERL Contact: Arvind Raghunathan
Research Areas: Control, OptimizationBrief- Arvind Raghunathan, Senior Principal Research Scientist in the Data Analytics group, received the IEEE Control Systems Society Roberto Tempo Best CDC Paper Award. The award was presented at the 2022 IEEE Conference on Decision & Control (CDC).
The award is given annually in honor of Roberto Tempo, the 44th President of the IEEE Control Systems Society (CSS). The Tempo Award Committee selects the best paper from the previous year's CDC based on originality, potential impact on any aspect of control theory, technology, or implementation, and for the clarity of writing. This year's award committee was headed by Prof. Patrizio Colaneri, Politecnico di Milano. Arvind's paper was nominated for the award by Prof. Lorenz Biegler, Carnegie Mellon University, with supporting letters from Prof. Andreas Waechter, Northwestern University, and Prof. Victor Zavala, University of Wisconsin-Madison.
- Arvind Raghunathan, Senior Principal Research Scientist in the Data Analytics group, received the IEEE Control Systems Society Roberto Tempo Best CDC Paper Award. The award was presented at the 2022 IEEE Conference on Decision & Control (CDC).
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AWARD Outstanding Presentation Award at the 28th Conference of Information Processing Society of Japan/Consumer Device & Systems Date: October 20, 2020
Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
MERL Contacts: Jianlin Guo; Philip V. Orlik
Research Areas: Communications, Optimization, Signal ProcessingBrief- MELCO and MERL researchers have won "Outstanding Presentation Award" at 28th Conference of Information Processing Society of Japan (IPSJ)/Consumer Device & Systems held on September 29-30, 2020. The paper titled "IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands" reports IEEE 802.19.3 standard development on coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. MERL and MELCO have been leading this standard development and made major technical contributions, which propose methods to mitigate interference in smart meter systems. The authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
See All Awards for Optimization -
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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 MERL at the International Conference on Robotics and Automation (ICRA) 2024 Date: May 13, 2024 - May 17, 2024
Where: Yokohama, Japan
MERL Contacts: Anoop Cherian; Radu Corcodel; Stefano Di Cairano; Chiori Hori; Siddarth Jain; Devesh K. Jha; Jonathan Le Roux; Diego Romeres; William S. Yerazunis
Research Areas: Artificial Intelligence, Machine Learning, Optimization, Robotics, Speech & AudioBrief- MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2024, which was held in Yokohama, Japan from May 13th to May 17th.
MERL was a Bronze sponsor of the conference, and exhibited a live robotic demonstration, which attracted a large audience. The demonstration showcased an Autonomous Robotic Assembly technology executed on MELCO's Assista robot arm and was the collaborative effort of the Optimization and Robotics Team together with the Advanced Technology department at Mitsubishi Electric.
MERL researchers from the Optimization and Robotics, Speech & Audio, and Control for Autonomy teams also presented 8 papers and 2 invited talks covering topics on robotic assembly, applications of LLMs to robotics, human robot interaction, safe and robust path planning for autonomous drones, transfer learning, perception and tactile sensing.
- MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2024, which was held in Yokohama, Japan from May 13th to May 17th.
See All News & Events for Optimization -
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Research Highlights
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Openings
See All Openings at MERL -
Recent Publications
- , "Decentralized, Safe, Multi-agent Motion Planning for Drones Under Uncertainty via Filtered Reinforcement Learning", IEEE Transactions on Control Systems Technology, 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,
- month = jan,
- url = {https://www.merl.com/publications/TR2024-136}
- }
- , "Chance-Constrained Optimization for Contact-rich Systems using Mixed Integer Programming", Nonlinear Analysis: Hybrid Systems, December 2024.BibTeX TR2024-008 PDF
- @article{Shirai2024dec,
- author = {Shirai, Yuki and Jha, Devesh K. and Raghunathan, Arvind and Romeres, Diego},
- title = {Chance-Constrained Optimization for Contact-rich Systems using Mixed Integer Programming},
- journal = {Nonlinear Analysis: Hybrid Systems},
- year = 2024,
- month = dec,
- url = {https://www.merl.com/publications/TR2024-008}
- }
- , "Integrating Generative Machine Learning Models and Physics-Based Models for Building Energy Simulation", American Modelica Conference, October 2024.BibTeX TR2024-140 PDF
- @inproceedings{Vanfretti2024oct,
- author = {Vanfretti, Luigi and Laughman, Christopher R. and Chakrabarty, Ankush}},
- title = {Integrating Generative Machine Learning Models and Physics-Based Models for Building Energy Simulation},
- booktitle = {American Modelica Conference},
- year = 2024,
- month = oct,
- url = {https://www.merl.com/publications/TR2024-140}
- }
- , "Reinforcement Learning-Based Estimation for Spatio-Temporal Systems", Nature Scientific Reports, DOI: 10.1038/s41598-024-72055-1, Vol. 14, pp. 22464, October 2024.BibTeX TR2024-134 PDF
- @article{Mowlavi2024oct,
- author = {Mowlavi, Saviz and Benosman, Mouhacine}},
- title = {Reinforcement Learning-Based Estimation for Spatio-Temporal Systems},
- journal = {Nature Scientific Reports},
- year = 2024,
- volume = 14,
- pages = 22464,
- month = oct,
- doi = {10.1038/s41598-024-72055-1},
- url = {https://www.merl.com/publications/TR2024-134}
- }
- , "ROSE-Opt: Robust and Efficient Analog Circuit Parameter Optimization with Knowledge-infused Reinforcement Learning", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, September 2024.BibTeX TR2024-132 PDF
- @article{Cao2024sep,
- author = {Cao, Weidong and Gao, Jian and Ma, Tianrui and Ma, Rui and Benosman, Mouhacine and Zhang, Xuan}},
- title = {ROSE-Opt: Robust and Efficient Analog Circuit Parameter Optimization with Knowledge-infused Reinforcement Learning},
- journal = {IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems},
- year = 2024,
- month = sep,
- url = {https://www.merl.com/publications/TR2024-132}
- }
- , "From Convexity to Strong Convexity and Beyond: Bridging The Gap In Convergence Rates", IEEE Conference on Decision and Control (CDC), September 2024.BibTeX TR2024-131 PDF
- @inproceedings{Romero2024sep,
- author = {Romero, Orlando and Benosman, Mouhacine and Pappas, George}},
- title = {From Convexity to Strong Convexity and Beyond: Bridging The Gap In Convergence Rates},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2024,
- month = sep,
- url = {https://www.merl.com/publications/TR2024-131}
- }
- , "Real-time Mixed-Integer Quadratic Programming for Vehicle Decision Making and Motion Planning", IEEE Transactions on Control Systems Technology, September 2024.BibTeX TR2024-123 PDF
- @article{Quirynen2024sep,
- author = {Quirynen, Rien and Safaoui, Sleiman and Di Cairano, Stefano}},
- title = {Real-time Mixed-Integer Quadratic Programming for Vehicle Decision Making and Motion Planning},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2024,
- month = sep,
- url = {https://www.merl.com/publications/TR2024-123}
- }
- , "MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models", International Conference on Automation Science and Engineering (CASE), August 2024.BibTeX TR2024-115 PDF
- @inproceedings{Yan2024aug,
- author = {Yan, Jiaqi and Chakrabarty, Ankush and Rupenyan, Alisa and Lygeros, John}},
- title = {MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models},
- booktitle = {International Conference on Automation Science and Engineering (CASE)},
- year = 2024,
- month = aug,
- url = {https://www.merl.com/publications/TR2024-115}
- }
- , "Decentralized, Safe, Multi-agent Motion Planning for Drones Under Uncertainty via Filtered Reinforcement Learning", IEEE Transactions on Control Systems Technology, January 2025.
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