News & Events

49 News items, Awards, Events or Talks found.



Learn about the MERL Seminar Series.



  •  NEWS    MERL work on 3D Printing in Orbit featured in IEEE Spectrum
    Date: June 3, 2022
    Where: IEEE Spectrum
    MERL Contacts: Avishai Weiss; William S. Yerazunis
    Research Areas: Applied Physics, Communications, Robotics
    Brief
    • MERL's research on on-orbit manufacturing was recently featured in an IEEE Spectrum article. The article, titled How Satellites Will 3D Print Their Own Antennas in Space gives an overview of MERL's efforts towards developing a system that construct spacecraft parts in their natural environment-- that is, in space. The technology, called OOM for On-Orbit Manufacturing, provides a way to manufacture not just antenna dishes, but general freeform sturctures on orbit and in a vacuum, using an solar-hardened resin based approach. This technology includes both a special high performance liquid resin, as well as a 3D freeform printer capable of building objects far larger than the as-launched satellite.

      An important aspect of the special resin is that all components have extremely low vapor pressures and do not boil away even in a vacuum. When exposed to solar ultraviolet, the resin hardens by polymerization crosslinking, forming a tough, rigid solid in a few seconds of exposure. No separate UV source is needed, making the entire process very energy efficient. Additionally, the crosslinking resin is heat resistant, and is unaffected to at least 400 degrees C. The 3D printer needed to print the resin is unlike common liquid-resin SLA printers- there is no vat of liquid resin, instead a shielded nozzle delivers the liquid resin directly to where the resin is needed. The result is the ability to construct large and very large structures, not just parabolic dishes, but also solar panel supports and structural trusswork, while in orbit. The system could even construct parts that were unanticipated during mission design and launch.

      MERL's On-Orbit Manufacturing Technology had previously been featured in a Mitsubishi Electric Corporation Press Release and was recently on display at a recent press exhibition in Tokyo, Japan.

      IEEE Spectrum is the flagship magazine and website of the IEEE, the world’s largest professional organization devoted to engineering and the applied sciences. IEEE Spectrum has a circulation of over 400,000 engineers worldwide, making it one of the leading science and engineering magazines.
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  •  NEWS    MERL researchers presented 5 papers and an invited workshop talk at ICRA 2022
    Date: May 23, 2022 - May 27, 2022
    Where: International Conference on Robotics and Automation (ICRA)
    MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Siddarth Jain; Devesh K. Jha; Pedro Miraldo; Daniel N. Nikovski; Rien Quirynen; Arvind Raghunathan; Diego Romeres; Abraham P. Vinod; Yebin Wang
    Research Areas: Artificial Intelligence, Machine Learning, Robotics
    Brief
    • MERL researchers presented 5 papers at the IEEE International Conference on Robotics and Automation (ICRA) that was held in Philadelphia from May 23-27, 2022. The papers covered a broad range of topics from manipulation, tactile sensing, planning and multi-agent control. The invited talk was presented in the "Workshop on Collaborative Robots and Work of the Future" which covered some of the work done by MERL researchers on collaborative robotic assembly. The workshop was co-organized by MERL, Mitsubishi Electric Automation's North America Development Center (NADC), and MIT.
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  •  TALK    [MERL Seminar Series 2022] Prof. Michael Posa presents talk titled Hybrid robotics and implicit learning
    Date & Time: Tuesday, May 3, 2022; 1:00 PM
    Speaker: Michael Posa, University of Pennsylvania
    MERL Host: Devesh K. Jha
    Research Areas: Control, Optimization, Robotics
    Abstract
    • Machine learning has shown incredible promise in robotics, with some notable recent demonstrations in manipulation and sim2real transfer. These results, however, require either an accurate a priori model (for simulation) or a large amount of data. In contrast, my lab is focused on enabling robots to enter novel environments and then, with minimal time to gather information, accomplish complex tasks. In this talk, I will argue that the hybrid or contact-driven nature of real-world robotics, where a robot must safely and quickly interact with objects, drives this high data requirement. In particular, the inductive biases inherent in standard learning methods fundamentally clash with the non-differentiable physics of contact-rich robotics. Focusing on model learning, or system identification, I will show both empirical and theoretical results which demonstrate that contact stiffness leads to poor training and generalization, leading to some healthy skepticism of simulation experiments trained on artificially soft environments. Fortunately, implicit learning formulations, which embed convex optimization problems, can dramatically reshape the optimization landscape for these stiff problems. By carefully reasoning about the roles of stiffness and discontinuity, and integrating non-smooth structures, we demonstrate dramatically improved learning performance. Within this family of approaches, ContactNets accurately identifies the geometry and dynamics of a six-sided cube bouncing, sliding, and rolling across a surface from only a handful of sample trajectories. Similarly, a piecewise-affine hybrid system with thousands of modes can be identified purely from state transitions. Time permitting, I'll discuss how these learned models can be deployed for control via recent results in real-time, multi-contact MPC.
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  •  NEWS    Radu Corcodel to present invited seminar at NYU on Robot Vision
    Date: May 4, 2022
    MERL Contact: Radu Corcodel
    Research Areas: Computer Vision, Robotics
    Brief
    • Radu Corcodel, a Principal Research Scientist in MERL's Computer Vision Group, will present an overview of the Robot Perception research published by MERL for advanced manipulation. The talk will mainly cover topics pertaining to robotic manipulation in unstructured environments such as machine vision, tactile sensing and autonomous grasping. The seminar will also cover specific perception problems in non-prehensile interactions such as Contact-Implicit Trajectory Optimization and Tactile Classification, and is intended for a broader audience.
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  •  NEWS    Devesh Jha delivers invited talk at Mechanical and Aerospace Engineering Department, NYU
    Date: March 1, 2022
    Where: Online/Zoom
    MERL Contact: Devesh K. Jha
    Research Areas: Artificial Intelligence, Machine Learning, Robotics
    Brief
    • Devesh Jha, a Principal Research Scientist in MERL's Data Analytics group, gave an invited talk at the Mechanical and Aerospace Engineering Department, NYU. The title of the talk was "Robotic Manipulation in the Wild: Planning, Learning and Control through Contacts". The talk presented some of the recent work done at MERL for robotic manipulation in unstructured environments in the presence of significant uncertainty.
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  •  NEWS    Radu Corcodel joins the IEEE-RAS Standing Committee for Standards & Human-Robot Interaction Terminology
    Date: February 3, 2022
    MERL Contact: Radu Corcodel
    Research Areas: Robotics, Human-Computer Interaction
    Brief
    • Radu Corcodel, a Principal Research Scientist in MERL's computer vision group, has been invited to join the IEEE-RAS Standing Committee for Standards & Human-Robot Interaction Terminology. This committee defines standard terms relevant to human-robot interaction in service, social, education, industrial, and research robotic applications. It establishes and defines a common terminology for practitioners and users of human-robot interaction (HRI) technologies. It is also intended to address issues common within the field of HRI, particularly surrounding the use of inconsistent and/or conflicting terms and definitions.

      The invitation is a recognition of Radu's excellent record of robotics research and a significant opportunity for him to contribute to new standards in robotics terminology.
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  •  EVENT    Prof. Melanie Zeilinger of ETH to give keynote at MERL's Virtual Open House
    Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
    Location: Virtual Event
    Speaker: Prof. Melanie Zeilinger, ETH
    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, Digital Video, Human-Computer Interaction, Information Security
    Brief
    • MERL is excited to announce the second keynote speaker for our Virtual Open House 2021:
      Prof. Melanie Zeilinger from ETH .

      Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

      Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Zeilinger's talk is scheduled for 3:15pm - 3:45pm (EST).

      Registration: https://mailchi.mp/merl/merlvoh2021

      Keynote Title: Control Meets Learning - On Performance, Safety and User Interaction

      Abstract: With increasing sensing and communication capabilities, physical systems today are becoming one of the largest generators of data, making learning a central component of autonomous control systems. While this paradigm shift offers tremendous opportunities to address new levels of system complexity, variability and user interaction, it also raises fundamental questions of learning in a closed-loop dynamical control system. In this talk, I will present some of our recent results showing how even safety-critical systems can leverage the potential of data. I will first briefly present concepts for using learning for automatic controller design and for a new safety framework that can equip any learning-based controller with safety guarantees. The second part will then discuss how expert and user information can be utilized to optimize system performance, where I will particularly highlight an approach developed together with MERL for personalizing the motion planning in autonomous driving to the individual driving style of a passenger.
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  •  EVENT    Prof. Ashok Veeraraghavan of Rice University to give keynote at MERL's Virtual Open House
    Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
    Location: Virtual Event
    Speaker: Prof. Ashok Veeraraghavan, Rice University
    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, Digital Video, Human-Computer Interaction, Information Security
    Brief
    • MERL is excited to announce the first keynote speaker for our Virtual Open House 2021:
      Prof. Ashok Veeraraghavan from Rice University.

      Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

      Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Veeraraghavan's talk is scheduled for 1:15pm - 1:45pm (EST).

      Registration: https://mailchi.mp/merl/merlvoh2021

      Keynote Title: Computational Imaging: Beyond the limits imposed by lenses.

      Abstract: The lens has long been a central element of cameras, since its early use in the mid-nineteenth century by Niepce, Talbot, and Daguerre. The role of the lens, from the Daguerrotype to modern digital cameras, is to refract light to achieve a one-to-one mapping between a point in the scene and a point on the sensor. This effect enables the sensor to compute a particular two-dimensional (2D) integral of the incident 4D light-field. We propose a radical departure from this practice and the many limitations it imposes. In the talk we focus on two inter-related research projects that attempt to go beyond lens-based imaging.

      First, we discuss our lab’s recent efforts to build flat, extremely thin imaging devices by replacing the lens in a conventional camera with an amplitude mask and computational reconstruction algorithms. These lensless cameras, called FlatCams can be less than a millimeter in thickness and enable applications where size, weight, thickness or cost are the driving factors. Second, we discuss high-resolution, long-distance imaging using Fourier Ptychography, where the need for a large aperture aberration corrected lens is replaced by a camera array and associated phase retrieval algorithms resulting again in order of magnitude reductions in size, weight and cost. Finally, I will spend a few minutes discussing how the wholistic computational imaging approach can be used to create ultra-high-resolution wavefront sensors.
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  •  EVENT    MERL Virtual Open House 2021
    Date & Time: Thursday, December 9, 2021; 100pm-5:30pm (EST)
    Location: Virtual Event
    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, Digital Video, Human-Computer Interaction, Information Security
    Brief
    • Mitsubishi Electric Research Laboratories cordially invites you to join our Virtual Open House, on December 9, 2021, 1:00pm - 5:30pm (EST).

      The event will feature keynotes, live sessions, research area booths, and time for open interactions with our researchers. Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities.

      Registration: https://mailchi.mp/merl/merlvoh2021
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  •  TALK    [MERL Seminar Series 2021] Dr. Hsiao-Yu (Fish) Tung presents talk at MERL entitled Learning to See by Moving: Self-supervising 3D scene representations for perception, control, and visual reasoning
    Date & Time: Tuesday, November 2, 2021; 1:00 PM EST
    Speaker: Dr. Hsiao-Yu (Fish) Tung, MIT BCS
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics
    Abstract
    • Current state-of-the-art CNNs can localize and name objects in internet photos, yet, they miss the basic knowledge that a two-year-old toddler has possessed: objects persist over time despite changes in the observer’s viewpoint or during cross-object occlusions; objects have 3D extent; solid objects do not pass through each other. In this talk, I will introduce neural architectures that learn to parse video streams of a static scene into world-centric 3D feature maps by disentangling camera motion from scene appearance. I will show the proposed architectures learn object permanence, can imagine RGB views from novel viewpoints in truly novel scenes, can conduct basic spatial reasoning and planning, can infer affordability in sentences, and can learn geometry-aware 3D concepts that allow pose-aware object recognition to happen with weak/sparse labels. Our experiments suggest that the proposed architectures are essential for the models to generalize across objects and locations, and it overcomes many limitations of 2D CNNs. I will show how we can use the proposed 3D representations to build machine perception and physical understanding more close to humans.
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  •  NEWS    Diego Romeres appointed as Associate Editor at ICRA 2022.
    Date: September 17, 2021 - October 31, 2021
    MERL Contact: Diego Romeres
    Research Areas: Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Optimization, Robotics
    Brief
    • Diego Romeres, a Principal Research Scientist in MERL's Data Analytics group, is serving as an Associate Editor (AE) for the IEEE International Conference on Robotics and Automation (ICRA) 2022.
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  •  NEWS    Anthony Vetro delivers keynote on robotic manipulation at inaugural IEEE Conference on Autonomous Systems
    Date: August 12, 2021
    MERL Contact: Anthony Vetro
    Research Areas: Artificial Intelligence, Computer Vision, Control, Dynamical Systems, Machine Learning, Optimization, Robotics
    Brief
    • Anthony Vetro gave a keynote at the inaugural IEEE Conference on Autonomous Systems (ICAS), which was held virtually from August 11-13, 2021. The talk focused on challenges and recent progress in the area of robotic manipulation. The conference is sponsored by IEEE Signal Processing Society (SPS) through the SPS Autonomous Systems Initiative.

      Abstract: Human-level manipulation continues to be beyond the capabilities of today’s robotic systems. Not only do current industrial robots require significant time to program a specific task, but they lack the flexibility to generalize to other tasks and be robust to changes in the environment. While collaborative robots help to reduce programming effort and improve the user interface, they still fall short on generalization and robustness. This talk will highlight recent advances in a number of key areas to improve the manipulation capabilities of autonomous robots, including methods to accurately model the dynamics of the robot and contact forces, sensors and signal processing algorithms to provide improved perception, optimization-based decision-making and control techniques, as well as new methods of interactivity to accelerate and enhance robot learning.
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  •  NEWS    MERL researchers Diego Romeres, Devesh Jha and Siddarth Jain co-organized a workshop on Robotic Manipulation at the RSS 2021 conference
    Date: July 13, 2021
    Where: Robotics: Science and Systems
    MERL Contacts: Siddarth Jain; Devesh K. Jha; Diego Romeres
    Research Areas: Artificial Intelligence, Machine Learning, Robotics
    Brief
    • MERL researchers Diego Romeres, Devesh Jha, and Siddarth Jain together with research groups at MIT, NVIDIA, NIST, TUM, Google DeepMind, ETH Zurich, Google AI, and UMASS Lowell organized a workshop at the Robotics: Science and Systems 2021 conference. The workshop was on "Advancing Artificial Intelligence and Manipulation for Robotics: Understanding Gaps, Industry and Academic Perspectives, and Community Building". The workshop had a list of excellent speakers both from academia and industry. Recording of the talks and of the panel discussion can be found in the link below.
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  •  NEWS    Karl Berntorp gave an invited lecture at University of Houston
    Date: April 22, 2021
    Where: Houston, Texas
    MERL Contact: Karl Berntorp
    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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  •  NEWS    Invited talk at University of Leeds
    Date: April 7, 2021
    Where: Online
    MERL Contact: Devesh K. Jha
    Research Areas: Artificial Intelligence, Machine Learning, Robotics
    Brief
    • Devesh Jha, a Principal Research Scientist in MERL's Data Analytics group, gave an invited talk at the robotics seminar series at the University of Leeds. The talk presented some of the recent work done at MERL in the areas of robotic manipulation and robot learning.
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  •  NEWS    Karl Berntorp gave an invited lecture at the Department of Electrical Engineering at Linköping University
    Date: April 6, 2021
    Where: Linköping University, Sweden
    MERL Contact: Karl Berntorp
    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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  •  NEWS    Diego Romeres appointed as an Associate Editor for IROS 2021
    Date: March 14, 2021 - April 20, 2021
    Where: IROS
    MERL Contact: Diego Romeres
    Research Areas: Artificial Intelligence, Data Analytics, Robotics
    Brief
    • Diego Romeres, a Principal Research Scientist in MERL's Data Analytics group, is serving as an Associate Editor (AE) for the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021).
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  •  NEWS    Stefano Di Cairano joins the Editorial Board of IEEE Transactions on Intelligent Vehicles
    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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  •  NEWS    Diego Romeres gave an invited talk at the Autonomy Talks at ETH, Zurich.
    Date: February 15, 2021
    Where: Virtual
    MERL Contact: Diego Romeres
    Research Areas: Artificial Intelligence, Machine Learning, Robotics
    Brief
    • Diego Romeres, a Principal Research Scientist in MERL's Data Analytics group, gave the invited talk "Reinforcement Learning for Robotics" at the Autonomy Talks organized at ETH, Zurich. In the presentation, some directions to apply Model-based Reinforcement Learning algorithms to real-world applications are presented together with a novel MBRL algorithm called MC-PILCO. The link to the presentation is https://www.youtube.com/watch?v=wYgbgMa4j-s.
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  •  EVENT    MERL Virtual Open House 2020
    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
    Brief
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  •  NEWS    New robotics benchmark system
    Date: November 16, 2020
    MERL Contacts: Devesh K. Jha; Daniel N. Nikovski; Diego Romeres
    Research Areas: Artificial Intelligence, Machine Learning, Robotics
    Brief
    • MERL researchers, in collaboration with researchers from MELCO and the Department of Brain and Cognitive Science at MIT, have released simulation software Circular Maze Environment (CME). This system could be used as a new benchmark for evaluating different control and robot learning algorithms. The control objective in this system is to tip and the tilt the maze so as to drive one (or multiple) marble(s) to the innermost ring of the circular maze. Although the system is very intuitive for humans to control, it is very challenging for artificial intelligence agents to learn efficiently. It poses several challenges for both model-based as well as model-free methods, due to its non-smooth dynamics, long planning horizon, and non-linear dynamics. The released Python package provides the simulation environment for the circular maze, where movement of multiple marbles could be simulated simultaneously. The package also provides a trajectory optimization algorithm to design a model-based controller in simulation.
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  •  NEWS    Devesh Jha appointed as an Associate Editor for IEEE Robotics and Automation Letters (RA-L).
    Date: October 29, 2020
    MERL Contact: Devesh K. Jha
    Research Areas: Artificial Intelligence, Machine Learning, Optimization, Robotics
    Brief
    • MERL Researcher Devesh Jha has been appointed to the editorial board of the IEEE Robotics and Automation Letters (RA-L) as an Associate Editor. IEEE RA-L publishes peer-reviewed articles in the areas of robotics and automation which can also be presented at the annual flagship conferences of RAS like ICRA, IROS and CASE.
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  •  NEWS    Computer vision and robotics researcher Siddarth Jain appointed as an Associate Editor for the IEEE Robotics and Automation Letters (RA-L)
    Date: October 13, 2020
    MERL Contact: Siddarth Jain
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics
    Brief
    • Computer vision and robotics researcher, Siddarth Jain, has been appointed to the editorial board of the IEEE Robotics and Automation Letters (RA-L) as an Associate Editor. Siddarth joined MERL in September 2019 after obtaining his Ph.D. in robotics from Northwestern University, where he developed novel robotics systems to help people with motor-impairments in performing activities of daily living tasks.

      RA-L publishes peer-reviewed articles in areas of robotics and automation. RA-L also provides a unique feature to the authors with the opportunity to publish a paper in a peer-reviewed journal and present the same paper at the annual flagship robotics conferences of IEEE RAS, including ICRA, IROS, and CASE.
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  •  NEWS    Karl Berntorp gave an invited lecture at the Department of Electrical Engineering at Linkoping University
    Date: October 8, 2020
    Where: Linkoping University
    MERL Contact: Karl Berntorp
    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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  •  NEWS    MERL Researcher Ankush Chakrabarty organized a special session on data-driven control at IEEE CCTA 2020
    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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