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
Awards
- 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; Yuki Shirai
  Research Areas: Artificial Intelligence, Optimization, Robotics
  Brief
  - 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.
- 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, Optimization
  Brief
  - 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.
- 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 Processing
  Brief
  - 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
News & Events
- NEWS MERL researchers present 9 papers at ACC 2024
  Date: July 10, 2024 - July 12, 2024
  Where: Toronto, Canada
  MERL Contacts: 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, Robotics
  Brief
  - 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.
- 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 & Audio
  Brief
  - 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.
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Research Highlights
- Edge-Assisted Internet of Vehicles for Smart Mobility
Internships
- MS0110: Internship - Stochastic MPC for Grid-Interactive Buildings and HVAC
  
  MERL is looking for a highly motivated and qualified candidate to work on stochastic control for grid-interactive net-zero energy buildings informed by deep generative models. The ideal candidate will have a strong understanding of optimization-based control with expertise demonstrated via, e.g., publications, in stochastic model predictive control.
  Additional understanding of energy systems and machine learning is a plus. Hands-on programming experience with numerical optimization solvers and Python fluency is required. The results of this 3-6 month internship are expected to be published in top-tier energy systems and/or control venues.
- CA0095: Internship - Infrastructure monitoring using quadrotors
  
  MERL seeks graduate students passionate about robotics to collaborate and develop a framework for infrastructure monitoring using quadrotors. The work will involve multi-domain research, including multi-agent planning and control, SLAM, and perception. The methods will be implemented and evaluated on an actual robotic platform (Crazyflies). The results of the internship are expected to be published in top-tier conferences and/or journals. The internship will take place during summer 2025 (exact dates are flexible) with an expected duration of 3-4 months.
  Please use your cover letter to explain how you meet the following requirements, preferably with links to papers, code repositories, etc., indicating your proficiency.
  Required Specific Experience
  - Current enrollment in a PhD program in Mechanical, Electrical Engineering, Computer Science, or related programs, with a focus on Robotics and/or Control Systems
  - Experience in some/all of these topics: multi-agent motion planning, constrained control, SLAM, computer vision
  - Experience with ROS2 and validation of algorithms on robotic platforms, preferably quadrotors
  - Strong programming skills in Python and/or C/C++
  Desired Specific Experience
  - Experience with Crazyflie quadrotors and the Crazyswarm library
  - Experience with the SLAM toolbox in ROS2
  - Experience in convex optimization and model predictive control
  - Experience with computer vision
- EA0065: Internship - Planning and Control of Mobile Manipulators
  
  MERL is seeking a highly motivated and qualified individual to conduct research in safe/robust whole-body motion planning and control of mobile manipulators. The ideal candidate should demonstrate solid background and track record of publications in the areas of robotic dynamics, motion planning, and control. Strong C++ and Python coding skills, knowledge of robotic software such as Pinocchio/Pybullet/MuJoCo, and optimization tools such as CasADi/PyTorch are a necessity. Ph.D. students in mechanical engineering, robotics, computer science, and electrical engineering are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.
  Required Specific Experience
  - Solid background and track record of conducting innovative research in the dynamic modeling, motion planning, and control of robotic systems.
  - Experience with C++/Python, Pinocchio, Pybullet, MuJoCo, CasADi, PyTorch.
See All Internships for Optimization
Openings
See All Openings at MERL
Recent Publications
- Vinod, A.P., Safaoui, S., Summers, T., Yoshikawa, N., Di Cairano, S., "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}
  - }
- Shirai, Y., Jha, D.K., Raghunathan, A., Romeres, D., "Chance-Constrained Optimization for Contact-rich Systems using Mixed Integer Programming", Nonlinear Analysis: Hybrid Systems, DOI: 10.1016/j.nahs.2024.101466, Vol. 52, 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,
  - volume = 52,
  - month = dec,
  - doi = {10.1016/j.nahs.2024.101466},
  - issn = {1751-570X},
  - url = {https://www.merl.com/publications/TR2024-008}
  - }
- Xiang, X., Palash, R., Yagyu, E., Dunham, S., Teo, K.H., Chowdhury, N., "AI-assisted Field Plate Design of GaN HEMT Device", Advanced Theory and Simulation, October 2024.
  BibTeX TR2024-152 PDF
  - @article{Xiang2024oct,
  - author = {Xiang, Xiaofeng and Palash, Rafid and Yagyu, Eiji and Dunham, Scott and Teo, Koon Hoo and Chowdhury, Nadim}},
  - title = {AI-assisted Field Plate Design of GaN HEMT Device},
  - journal = {Advanced Theory and Simulation},
  - year = 2024,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2024-152}
  - }
- Sun, H., Kosanic, M., Kawano, S., Raghunathan, A., Kitamura, S., Takaguchi, Y., "Proactive Sequential Phase Swapping Scheduling for Distribution Systems with a Finite Horizon", IEEE PES Asia-Pacific Power and Energy Engineering Conference, October 2024.
  BibTeX TR2024-149 PDF
  - @inproceedings{Sun2024oct,
  - author = {Sun, Hongbo and Kosanic, Miroslav and Kawano, Shunsuke and Raghunathan, Arvind and Kitamura, Shoichi and Takaguchi, Yusuke}},
  - title = {Proactive Sequential Phase Swapping Scheduling for Distribution Systems with a Finite Horizon},
  - booktitle = {IEEE PES Asia-Pacific Power and Energy Engineering Conference},
  - year = 2024,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2024-149}
  - }
- Bortoff, S.A., Laughman, C.R., Deshpande, V.M., Qiao, H., "Fluid Property Functions in Polar and Parabolic Coordinates", American Modelica Conference, October 2024.
  BibTeX TR2024-144 PDF
  - @inproceedings{Bortoff2024oct,
  - author = {Bortoff, Scott A. and Laughman, Christopher R. and Deshpande, Vedang M. and Qiao, Hongtao}},
  - title = {Fluid Property Functions in Polar and Parabolic Coordinates},
  - booktitle = {American Modelica Conference},
  - year = 2024,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2024-144}
  - }
- Kosanic, M., Sun, H., Kawano, S., Raghunathan, A., Kitamura, S., "Sequentially Pruning Phase Rebalance Schedule: Load Profile Learning Approach", IEEE PES Innovative Smart Grid Technologies Conference - Europe (ISGT Europe), October 2024.
  BibTeX TR2024-143 PDF
  - @inproceedings{Kosanic2024oct,
  - author = {Kosanic, Miroslav and Sun, Hongbo and Kawano, Shunsuke and Raghunathan, Arvind and Kitamura, Shoichi}},
  - title = {Sequentially Pruning Phase Rebalance Schedule: Load Profile Learning Approach},
  - booktitle = {IEEE PES Innovative Smart Grid Technologies Conference - Europe (ISGT Europe)},
  - year = 2024,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2024-143}
  - }
- Vanfretti, L., Laughman, C.R., Chakrabarty, A., "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}
  - }
- Mowlavi, S., Benosman, M., "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}
  - }
See All Publications for Optimization
Videos

Description of the abort-safe spacecraft rendezvous example

Decentralized, Safe, Multi-agent Motion Planning for Drones Under Uncertainty via Filtered Reinforcement Learning

[MERL Seminar Series Fall 2023] Co-Design of Complex Systems: From Autonomy to Future Mobility

[MERL Seminar Series Fall 2023] Composable Optimization for Robotic Simulation, Planning, and Control

[MERL Seminar Series Fall 2023] A Process Systems Engineering Perspective on Carbon Capture: Key Challenges and Opportunities

[TRO 2024] Safe Multiagent Motion Planning Under Uncertainty for Drones Using Filtered Reinforcement Learning

Simultaneous Trajectory Optimization and Contact Selection for Multi-Modal Manipulation Planning

[MERL Seminar Series Spring 2023] Learning and Dynamical Systems

Robust Pivoting Manipulation using Contact Implicit Bilevel Optimization

Robot Locomotion by Automated Controller Tuning

Real-time Mixed-integer Programming for Vehicle Decision Making and Motion Planning

Optimization-based Coordination and Control of Traffic Lights and Mixed Traffic in Multi-Intersection Networks

[MERL Seminar Series Fall 2022] Design, Identification and Simulation of PM Synchronous Machines for Traction

Toshiaki Koike-Akino Gives Seminar Talk at IEEE Boston Photonics

[MERL Seminar Series Spring 2022] RLMPC: An Ideal Combination of Formal Optimal Control and Reinforcement Learning?

[MERL Seminar Series Spring 2022] Extreme optics design as a large-scale optimization problem

[MERL Seminar Series 2021] Integration of Analytics Techniques for Algorithmic Sports Betting

Multiview Sensing with Unknown Permutations: An Optimal Transport Approach

Imaging for inverse scattering in Reflection Tomography

Electric Satellite Station Keeping, Attitude Control, and Momentum Management by MPC

Polar Coding with Chemical Reaction Networks for Molecular Communications

EMI reduction in PWM inverters using adaptive frequency modulated carriers

Fast Pattern Search in Big Data

Five Axis Additive Manufacturing

Globally Optimal Power Flow
Software & Data Downloads