News & Events

74 News items, Awards, Events or Talks found.



Learn about the MERL Seminar Series.



  •  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    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, Robotics
    Brief
    • 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.
  •  
  •  NEWS    Saviz Mowlavi gave an invited talk at North Carolina State University
    Date: April 12, 2024
    MERL Contact: Saviz Mowlavi
    Research Areas: Control, Dynamical Systems, Machine Learning, Optimization
    Brief
    • Saviz Mowlavi was invited to present remotely at the Computational and Applied Mathematics seminar series in the Department of Mathematics at North Carolina State University.

      The talk, entitled "Model-based and data-driven prediction and control of spatio-temporal systems", described the use of temporal smoothness to regularize the training of fast surrogate models for PDEs, user-friendly methods for PDE-constrained optimization, and efficient strategies for learning feedback controllers for PDEs.
  •  
  •  TALK    [MERL Seminar Series 2024] Na Li presents talk titled Close the Loop: From Data to Actions in Complex Systems
    Date & Time: Wednesday, April 10, 2024; 12:00 PM
    Speaker: Na Li, Harvard University
    MERL Host: Yebin Wang
    Research Areas: Control, Dynamical Systems, Machine Learning
    Abstract
    • The explosive growth of machine learning and data-driven methodologies have revolutionized numerous fields. Yet, translating these successes to the domain of dynamical, physical systems remains a significant challenge, hindered by the complex and often unpredictable nature of such environments. Closing the loop from data to actions in these systems faces many difficulties, stemming from the need for sample efficiency and computational feasibility amidst intricate dynamics, along with many other requirements such as verifiability, robustness, and safety. In this talk, we bridge this gap by introducing innovative approaches that harness representation-based methods, domain knowledge, and the physical structures of systems. We present a comprehensive framework that integrates these components to develop reinforcement learning and control strategies that are not only tailored for the complexities of physical systems but also achieve efficiency, safety, and robustness with provable performance.
  •  
  •  TALK    [MERL Seminar Series 2024] Fadel Adib presents talk titled Decoding Hidden Worlds: Unprecedented Sensing and Connectivity for Climate, Robotics, & Smart Environments
    Date & Time: Wednesday, April 3, 2024; 12:00 PM
    Speaker: Fadel Adib, MIT & Cartesian
    MERL Host: Wael Hajj Ali
    Research Areas: Computational Sensing, Dynamical Systems, Signal Processing
    Abstract
    • This talk will cover a new generation of technologies that can sense, connect, and perceive the physical world in unprecedented ways. These technologies can uncover hidden worlds around us, promising transformative impact on areas spanning climate change monitoring, ocean mapping, healthcare, food security, supply chain, and even extraterrestrial exploration.

      The talk will cover four core technologies invented by Prof. Adib and his team. The first is an ocean internet-of-things (IoT) that uses battery-free sensors for climate change monitoring, marine life discovery, and seafood production (aquaculture). The second is a new perception technology that enables robots to sense and manipulate hidden objects. The third is a new augmented reality headset with ``X-ray vision”, which extends human perception beyond line-of-sight. The fourth is a wireless sensing technology that can “see through walls” and monitor people’s vital signs (including their breathing, heart rate, and emotions), enabling smart environments that sense humans requiring any contact with the human body.

      The talk will touch on the journey of these technologies from their inception at MIT to international collaborations and startups that are translating them to real-world impact in areas spanning healthcare, climate change, and supply chain.
  •  
  •  NEWS    Ankush Chakrabarty gave a lecture at UT-Austin's Seminar Series on Occupant-Centric Grid-Interactive Buildings
    Date: March 20, 2024
    Where: Austin, TX
    MERL Contact: Ankush Chakrabarty
    Research Areas: Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization
    Brief
    • Ankush Chakrabarty, Principal Research Scientist in the Multiphysical Systems Team, was invited to speak as a guest lecturer in the seminar series on "Occupant-Centric Grid Interactive Buildings" in the Department of Civil, Architectural and Environmental Engineering (CAEE) at the University of Texas at Austin.

      The talk, entitled "Deep Generative Networks and Fine-Tuning for Net-Zero Energy Buildings" described lessons learned from MERL's recent research on generative models for building simulation and control, along with meta-learning for on-the-fly fine-tuning to adapt and optimize energy expenditure.
  •  
  •  NEWS    Karl Berntorp joins the Editorial Board of IEEE Transactions on Control Systems Technology
    Date: December 7, 2023
    Research Areas: Control, Dynamical Systems
    Brief
    • Karl Berntorp has joined the Editorial Board of the IEEE Transactions on Control Systems Technology (T-CST) as an Associate Editor. The IEEE T-CST publishes peer-reviewed papers on technological advances in the design, realization, and operation of control systems, and bridges the gap between the theory and practice of control engineering.
  •  
  •  TALK    [MERL Seminar Series 2023] Gioele Zardini presents talk titled Co-Design of Complex Systems: From Autonomy to Future Mobility
    Date & Time: Tuesday, November 21, 2023; 11:00 AM
    Speaker: Gioele Zardini, ETH Zürich and MIT
    Research Areas: Control, Dynamical Systems
    Abstract
    • When designing complex systems, we need to consider multiple trade-offs at various abstraction levels and scales, and choices of single components need to be studied jointly. For instance, the design of future mobility solutions (e.g., autonomous vehicles, micromobility) and the design of the mobility systems they enable are closely coupled. Indeed, knowledge about the intended service of novel mobility solutions would impact their design and deployment process, whilst insights about their technological development could significantly affect transportation management policies. Optimally co-designing sociotechnical systems is a complex task for at least two reasons. On one hand, the co-design of interconnected systems (e.g., large networks of cyber-physical systems) involves the simultaneous choice of components arising from heterogeneous natures (e.g., hardware vs. software parts) and fields, while satisfying systemic constraints and accounting for multiple objectives. On the other hand, components are connected via collaborative and conflicting interactions between different stakeholders (e.g., within an intermodal mobility system). In this talk, I will present a framework to co-design complex systems, leveraging a monotone theory of co-design and tools from game theory. The framework will be instantiated in the task of designing future mobility systems, all the way from the policies that a city can design, to the autonomy of vehicles part of an autonomous mobility-on-demand service. Through various case studies, I will show how the proposed approaches allow one to efficiently answer heterogeneous questions, unifying different modeling techniques and promoting interdisciplinarity, modularity, and compositionality. I will then discuss open challenges for compositional systems design optimization, and present my agenda to tackle them.
  •  
  •  TALK    [MERL Seminar Series 2023] Prof. Shaoshuai Mou presents talk titled Inverse Optimal Control for Autonomous Systems
    Date & Time: Tuesday, October 10, 2023; 1:00 PM
    Speaker: Shaoshuai Mou, Purdue University
    MERL Host: Yebin Wang
    Research Areas: Control, Dynamical Systems, Robotics
    Abstract
    • Inverse Optimal Control (IOC) aims to achieve an objective function corresponding to a certain task from an expert robot driven by optimal control, which has become a powerful tool in many applications in robotics. We will present our recent solutions to IOC based on incomplete observations of systems' trajectories, which enables an autonomous system to “sense-and-adapt", i.e., incrementally improving the learning of objective functions as new data arrives. This also leads to a distributed algorithm to solve IOC in multi-agent systems, in which each agent can only access part of the overall trajectory of an optimal control system and cannot solve IOC by itself. This is perhaps the first distributed method to IOC. Applications of IOC into human prediction will also be given.
  •  
  •  NEWS    MERL presents 9 papers at 2023 IFAC World Congress
    Date: July 9, 2023 - July 14, 2023
    MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Christopher R. Laughman; Diego Romeres; Abraham P. Vinod
    Research Areas: Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics
    Brief
    • MERL researchers presented 9 papers and organized 2 invited/workshop sessions at the 2023 IFAC World Congress held in Yokohama, JP.

      MERL's contributions covered topics including decision-making for autonomous vehicles, statistical and learning-based estimation for GNSS and energy systems, impedance control for delta robots, learning for system identification of rigid body dynamics and time-varying systems, and meta-learning for deep state-space modeling using data from similar systems. The invited session (MERL co-organizer: Ankush Chakrabarty) was on the topic of “Estimation and observer design: theory and applications” and the workshop (MERL co-organizer: Karl Berntorp) was on “Gaussian Process Learning for Systems and Control”.
  •  
  •  NEWS    Keynote address given by Philip Orlik at 9th annual IEEE Smartcomp conference
    Date: June 26, 2023
    Where: International Conference on Smart Computing (SMARTCOMP), Vanderbilt University, Nashville, Tennessee
    MERL Contact: Philip V. Orlik
    Research Areas: Communications, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Signal Processing
    Brief
    • VP & Research Director, Philip Orlik, gave a keynote titled, "Smart Technologies for Smarter Buildings" at the 9th edition of the IEEE International Conference on Smart Computing (SMARTCOMP) focusing on some of the research challenges and opportunities that arise as we seek to achieve net-zero emissions in Smart building environments.

      SMARTCOMP is the premier conference on smart computing. Smart computing is a multidisciplinary domain based on the synergistic influence of advances in sensor-based technologies, Internet of Things, cyber-physical systems, edge computing, big data analytics, machine learning, cognitive computing, and artificial intelligence.
  •  
  •  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 Processing
    Brief
    • 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.
  •  
  •  NEWS    Abraham Vinod gave an invited talk at the University of California Santa Cruz
    Date: June 8, 2023
    Where: Zoom
    MERL Contact: Abraham P. Vinod
    Research Areas: Artificial Intelligence, Control, Dynamical Systems, Optimization, Robotics
    Brief
    • Abraham Vinod gave an invited talk at the Electrical and Computer Engineering Department, the University of California Santa Cruz, titled "Motion Planning under Constraints and Uncertainty using Data and Reachability". His presentation covered recent work on fast and safe motion planners that can allow for coordination among agents, mitigate uncertainty arising from sensing limitations and simplified models, and tolerate the possibility of failures.
  •  
  •  NEWS    Ankush Chakrabarty co-organized three sessions at the ACC2023, and was nominated for Best Energy Systems Paper.
    Date: June 30, 2023 - June 2, 2023
    Where: San Diego, CA
    MERL Contact: Ankush Chakrabarty
    Research Areas: Applied Physics, Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics
    Brief
    • Ankush Chakrabarty (researcher, Multiphysical Systems Team) co-organized and spoke at 3 sessions at the 2023 American Control Conference in San Diego, CA. These include: (1) A tutorial session (w/ Stefano Di Cairano) on "Physics Informed Machine Learning for Modeling and Control": an effort with contributions from multiple academic institutes and US research labs; (2) An invited session on "Energy Efficiency in Smart Buildings and Cities" in which his paper (w/ Chris Laughman) on "Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems" was nominated for Best Energy Systems Paper Award; and, (3) A special session on Diversity, Equity, and Inclusion to improve recruitment and retention of underrepresented groups in STEM research.
  •  
  •  TALK    [MERL Seminar Series 2023] Dr. Michael Muehlebach presents talk titled Learning and Dynamical Systems
    Date & Time: Tuesday, April 11, 2023; 11:00 AM
    Speaker: Michael Muehlebach, Max Planck Institute for Intelligent Systems
    Research Areas: Control, Dynamical Systems, Machine Learning, Optimization, Robotics
    Abstract
    • The talk will be divided into two parts. The first part of the talk introduces a class of first-order methods for constrained optimization that are based on an analogy to non-smooth dynamical systems. The key underlying idea is to express constraints in terms of velocities instead of positions, which has the algorithmic consequence that optimizations over feasible sets at each iteration are replaced with optimizations over local, sparse convex approximations. This results is a simplified suite of algorithms and an expanded range of possible applications in machine learning. In the second part of my talk, I will present a robot learning algorithm for trajectory tracking. The method incorporates prior knowledge about the system dynamics and by optimizing over feedforward actions, the risk of instability during deployment is mitigated. The algorithm will be evaluated on a ping-pong playing robot that is actuated by soft pneumatic muscles.
  •  
  •  NEWS    MERL researchers presenting workshop papers at NeurIPS 2022
    Date: December 2, 2022 - December 8, 2022
    MERL Contacts: Matthew Brand; Toshiaki Koike-Akino; Jing Liu; Saviz Mowlavi; Kieran Parsons; Ye Wang
    Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning, Signal Processing
    Brief
    • In addition to 5 papers in recent news (https://www.merl.com/news/news-20221129-1450), MERL researchers presented 2 papers at the NeurIPS Conference Workshop, which was held Dec. 2-8. NeurIPS is one of the most prestigious and competitive international conferences in machine learning.

      - “Optimal control of PDEs using physics-informed neural networks” by Saviz Mowlavi and Saleh Nabi

      Physics-informed neural networks (PINNs) have recently become a popular method for solving forward and inverse problems governed by partial differential equations (PDEs). By incorporating the residual of the PDE into the loss function of a neural network-based surrogate model for the unknown state, PINNs can seamlessly blend measurement data with physical constraints. Here, we extend this framework to PDE-constrained optimal control problems, for which the governing PDE is fully known and the goal is to find a control variable that minimizes a desired cost objective. We validate the performance of the PINN framework by comparing it to state-of-the-art adjoint-based optimization, which performs gradient descent on the discretized control variable while satisfying the discretized PDE.

      - “Learning with noisy labels using low-dimensional model trajectory” by Vasu Singla, Shuchin Aeron, Toshiaki Koike-Akino, Matthew E. Brand, Kieran Parsons, Ye Wang

      Noisy annotations in real-world datasets pose a challenge for training deep neural networks (DNNs), detrimentally impacting generalization performance as incorrect labels may be memorized. In this work, we probe the observations that early stopping and low-dimensional subspace learning can help address this issue. First, we show that a prior method is sensitive to the early stopping hyper-parameter. Second, we investigate the effectiveness of PCA, for approximating the optimization trajectory under noisy label information. We propose to estimate the low-rank subspace through robust and structured variants of PCA, namely Robust PCA, and Sparse PCA. We find that the subspace estimated through these variants can be less sensitive to early stopping, and can outperform PCA to achieve better test error when trained on noisy labels.

      - In addition, new MERL researcher, Jing Liu, also presented a paper entitled “CoPur: Certifiably Robust Collaborative Inference via Feature Purification" based on his previous work before joining MERL. His paper was elected as a spotlight paper to be highlighted in lightening talks and featured paper panel.
  •  
  •  EVENT    MERL's Virtual Open House 2022
    Date & Time: Monday, December 12, 2022; 1:00pm-5:30pm ET
    Location: Mitsubishi Electric Research Laboratories (MERL)/Virtual
    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
    Brief
    • Join MERL's virtual open house on December 12th, 2022! Featuring a keynote, live sessions, research area booths, and opportunities to interact with our research team. Discover who we are and what we do, and learn about internship and employment opportunities.
  •  
  •  NEWS    Rien Quirynen to give an invited talk at the University of California Santa Cruz
    Date: November 14, 2022
    Where: Zoom
    Research Areas: Control, Dynamical Systems, Optimization, Robotics
    Brief
    • Rien Quirynen will give an invited talk at the Electrical and Computer Engineering Department, University of California Santa Cruz on "Real-time Motion Planning and Predictive Control by Mixed-integer Programming for Autonomous Vehicles". The talk will present recent work on a tailored branch-and-bound method for real-time motion planning and decision making on embedded processing units, and recent results for two applications related to automated driving and traffic control.
  •  
  •  NEWS    Avishai Weiss to give an invited talk at the University of Kentucky
    Date: November 11, 2022
    MERL Contact: Avishai Weiss
    Research Areas: Control, Dynamical Systems, Optimization
    Brief
    • Avishai Weiss will give an invited talk at the William Maxwell Reed Seminar Series, Mechanical and Aerospace Engineering Department, University of Kentucky on "Fail-Safe Spacecraft Rendezvous." The talk will present some recent developments at MERL on guaranteeing safe rendezvous trajectories that avoid colliding with the target in the event of thruster anomalies.
  •  
  •  TALK    [MERL Seminar Series 2022] Prof. Ufuk Topcu presents talk titled Autonomous systems in the intersection of formal methods, learning, and control
    Date & Time: Wednesday, October 26, 2022; 1:00 PM
    Speaker: Ufuk Topcu, The University of Texas at Austin
    MERL Host: Abraham P. Vinod
    Research Areas: Control, Dynamical Systems, Optimization
    Abstract
    • Autonomous systems are emerging as a driving technology for countlessly many applications. Numerous disciplines tackle the challenges toward making these systems trustworthy, adaptable, user-friendly, and economical. On the other hand, the existing disciplinary boundaries delay and possibly even obstruct progress. I argue that the nonconventional problems that arise in designing and verifying autonomous systems require hybrid solutions in the intersection of learning, formal methods, and controls. I will present examples of such hybrid solutions in the context of learning in sequential decision-making processes. These results offer novel means for effectively integrating physics-based, contextual, or structural prior knowledge into data-driven learning algorithms. They improve data efficiency by several orders of magnitude and generalizability to environments and tasks that the system had not experienced previously.
  •  
  •  NEWS    Stefano Di Cairano to give a public lecture on status and challenges of automotive driving at IEEE CSS Day
    Date: October 24, 2022
    Where: Online, 10/24/2022 9:00am (Eastern time)
    MERL Contact: Stefano Di Cairano
    Research Areas: Control, Dynamical Systems, Optimization, Robotics
    Brief
    • Dr. Stefano Di Cairano (Senior Team Leader at MERL) has been invited to give a public talk at the first IEEE CSS Day event on the status, challenges, and role of control in autonomous driving.

      The talk, titled "The Long Voyage Towards Autonomous Driving, with Control Systems as the Co-Pilot", will review some history of autonomous driving, some of the open challenges that control technology may help address, and the next steps towards full-autonomy. The talk is designed for a non-technical audience, to explain the role and impact of control in automated driving technology.
  •  
  •  NEWS    MERL Researcher Interviewed by Globest.com about "High Tech Airflow Control for Smarter Energy Use"
    Date: August 25, 2022
    MERL Contact: Anthony Vetro
    Research Areas: Dynamical Systems, Machine Learning, Multi-Physical Modeling
    Brief
    • MERL researcher Saleh Nabi was interviewed by Globest.com regarding the use of airflow optimization for smarter energy use and disease prevention. The article titled "High Tech Airflow Control for Smarter Energy Use: Reducing costs and improving effectiveness means a lot of tricky math" was recently published and describes how the solutions to complex fluid dynamical equations leads to improved HVAC control.

      Globest.com is a trusted and independent team of experts providing commercial real estate professionals with comprehensive coverage and best practices necessary to innovate and build their businesses. More details about Globest can be found here: https://www.globest.com/static/about-us/
  •  
  •  NEWS    MERL launches Postdoctoral Research Fellow program
    Date: September 21, 2022
    MERL Contacts: Philip V. Orlik; 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
    • Mitsubishi Electric Research Laboratories (MERL) invites qualified postdoctoral candidates to apply for the position of Postdoctoral Research Fellow. This position provides early career scientists the opportunity to work at a unique, academically-oriented industrial research laboratory. Successful candidates will be expected to define and pursue their own original research agenda, explore connections to established laboratory initiatives, and publish high impact articles in leading venues. Please refer to our web page for further details.
  •  
  •  NEWS    Yebin Wang appointed as an Associate Editor for ICRA 2023.
    Date: September 15, 2022
    MERL Contact: Yebin Wang
    Research Areas: Control, Dynamical Systems, Robotics
    Brief
    • Yebin Wang, a Senior Principal Research Scientist in MERL's Electric Machines and Devices, is serving as an Associate Editor for the IEEE International Conference on Robotics and Automation (ICRA) 2023.


      As the flagship conference of the IEEE Robotics and Automation Society, ICRA will bring together the world's top researchers and most important companies to share ideas and advances in our field.
  •  
  •  AWARD    Marcus Greiff receives Outstanding Student Paper Award at CCTA 2022
    Date: August 25, 2022
    Awarded to: Marcus Greiff
    Research Areas: Control, Dynamical Systems, Robotics
    Brief
    • Marcus Greiff, a Visiting Research Scientist at MERL, was awarded one of three outstanding student paper awards at the IEEE CCTA 2022 conference for his paper titled "Quadrotor Control on SU(2)xR3 with SLAM Integration". The award was given for originality, clarity, and potential impact on practical applications of control. The work presents a complete UAV control system design, facilitating autonomous supermarket inventorying without the need for external motion capture systems. A video of the experiments is on YouTube, including both simulations and real-time examples.
  •