Robotics
Where hardware, software and machine intelligence come together.
Our research is interdisciplinary and focuses on sensing, planning, reasoning, and control of single and multi-agent systems, including both manipulation and mobile robots. We strive to develop algorithms and methods for factory automation, smart building and transportation applications using machine learning, computer vision, RF/optical sensing, wireless communications, control theory and signal processing. Key research themes include bin picking and object manipulation, sensing and mapping of indoor areas, coordinated control of robot swarms, as well as robot learning and simulation.
Quick Links
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Researchers
Devesh K.
Jha
Diego
Romeres
Daniel N.
Nikovski
Arvind
Raghunathan
Stefano
Di Cairano
Yebin
Wang
Mouhacine
Benosman
Toshiaki
Koike-Akino
William S.
Yerazunis
Karl
Berntorp
Scott A.
Bortoff
Radu
Corcodel
Siddarth
Jain
Tim K.
Marks
Ye
Wang
Matthew E.
Brand
Rien
Quirynen
Bingnan
Wang
Avishai
Weiss
Jianlin
Guo
Jonathan
Le Roux
Hassan
Mansour
Marcel
Menner
Philip V.
Orlik
Koon Hoo
Teo
Anthony
Vetro
Pedro
Miraldo
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Awards
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AWARD Best student paper award at RSS22 Date: June 29, 2022
Awarded to: Weizhe Chen
MERL Contact: Diego Romeres
Research Area: RoboticsBrief- Weizhe Chen, a current intern at MERL from Indiana University, Bloomington, Indiana, USA, won the best student paper award at the Robotics Science and Systems (RSS) 2022 conference. The research at Weizhe Chen's university leading up to the awarded paper titled 'AK: Attentive Kernel for Information Gathering', proposes a novel non stationary kernel called, Attentive Kernel, for Gaussian Process Regression. The novel kernel is used to guide a planner to accumulate more valuable data in an elevation mapping task.
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AWARD MERL Researcher Devesh Jha Wins the Rudolf Kalman Best Paper Award 2019 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, RoboticsBrief- 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.
See All Awards for MERL -
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News & Events
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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 VideoBrief- 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.
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NEWS Rien Quirynen to give an invited talk at the University of California Santa Cruz Date: November 14, 2022
Where: Zoom
MERL Contact: Rien Quirynen
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- 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.
See All News & Events for Robotics -
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Internships
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CV1938: Component transfer learning for RL and robotic applications
MERL is offering a new research internship opportunity in the field of Transfer Learning for Deep RL. The position requires a strong background in Deep RL, excellent programming skills and experience with robotics is preferred. The position is open to graduate students on a PhD track only, and the length of the internship is three months with the possibility of extending if required. The intern is expected to disseminate this research in top tier scientific conferences such as RSS, IROS, ICRA etc., and if applicable, help with filing associated patents. Start and end dates are flexible.
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MD1886: Co-design of robotic arm and control systems
MERL is seeking a highly motivated and qualified individual to conduct research in model-based robotic system design. The ideal candidate should have solid backgrounds in robotic dynamics and simulation, motion planning and control, simulation-based optimization, surrogate modeling, and coding skills. Demonstrated experience on implementing robotic dynamics and simulation/optimization software such as Matlab is 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.
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CI1948: Human-Machine Interface with Biosignal Processing
MERL is seeking an intern to work on research for human-machine interface with multi-modal bio-sensors. The ideal candidate is an experienced PhD student or post-graduate researcher having an excellent background in brain-machine interface (BMI), deep learning, mixed reality (XR), remote robot manipulation, and bio sensing. The expected duration of the internship is 3-6 months, with a flexible start date.
See All Internships for Robotics -
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Recent Publications
- , "1 Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application", IEEE Transaction on Robotics, December 2022.BibTeX TR2022-154 PDF
- @article{Romeres2022dec,
- author = {Amadio, Fabio and Dalla Libera, Alberto and Antonello, Riccardo and Nikovski, Daniel N. and Carli, Ruggero and Romeres, Diego},
- title = {1 Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application},
- journal = {IEEE Transaction on Robotics},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-154}
- }
- , "Active Exploration for Robotic Manipulation", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2022.BibTeX TR2022-139 PDF
- @inproceedings{Schneider2022oct,
- author = {Schneider, Tim and Belousov, Boris and Chalvatzaki, Georgia and Romeres, Diego and Jha, Devesh K. and Peters, Jan},
- title = {Active Exploration for Robotic Manipulation},
- booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-139}
- }
- , "Motion Planning and Model Predictive Control for Automated Tractor-Trailer Hitching Maneuver", IEEE Conference on Control Technology and Applications (CCTA), August 2022.BibTeX TR2022-109 PDF
- @inproceedings{Wang2022aug,
- author = {Wang, Zejiang and Ahmad, Ahmad and Quirynen, Rien and Wang, Yebin and Bhagat, Akshay and Zeino, Eyad and Zushi, Yuji and Di Cairano, Stefano},
- title = {Motion Planning and Model Predictive Control for Automated Tractor-Trailer Hitching Maneuver},
- booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
- year = 2022,
- month = aug,
- url = {https://www.merl.com/publications/TR2022-109}
- }
- , "Imitation and Supervised Learning of Compliance for Robotic Assembly", European Control Conference (ECC), DOI: 10.23919/ECC55457.2022.9838102, July 2022, pp. 1882-1889.BibTeX TR2022-099 PDF Video
- @inproceedings{Jha2022jul,
- author = {Jha, Devesh K. and Romeres, Diego and Yerazunis, William S. and Nikovski, Daniel N.},
- title = {Imitation and Supervised Learning of Compliance for Robotic Assembly},
- booktitle = {European Control Conference (ECC)},
- year = 2022,
- pages = {1882--1889},
- month = jul,
- publisher = {IEEE},
- doi = {10.23919/ECC55457.2022.9838102},
- isbn = {978-3-9071-4407-7},
- url = {https://www.merl.com/publications/TR2022-099}
- }
- , "EEG-GAT: Graph Attention Networks for Classification of Electroencephalogram (EEG) Signals", International Conference of the IEEE Engineering in Medicine & Biology Society (EMBS), DOI: 10.1109/EMBC48229.2022.9871984, July 2022.BibTeX TR2022-097 PDF
- @inproceedings{Demir2022jul,
- author = {Demir, Andac and Koike-Akino, Toshiaki and Wang, Ye and Erdogmus, Deniz},
- title = {EEG-GAT: Graph Attention Networks for Classification of Electroencephalogram (EEG) Signals},
- booktitle = {International Conference of the IEEE Engineering in Medicine & Biology Society (EMBS)},
- year = 2022,
- month = jul,
- publisher = {IEEE},
- doi = {10.1109/EMBC48229.2022.9871984},
- issn = {2694-0604},
- isbn = {978-1-7281-2782-8},
- url = {https://www.merl.com/publications/TR2022-097}
- }
- , "Python-based Open Source Package for Optimization of Contact-rich Systems", Robotics: Science and Systems, June 2022.BibTeX TR2022-089 PDF
- @inproceedings{Raghunathan2022jun,
- author = {Raghunathan, Arvind and Jha, Devesh K. and Romeres, Diego},
- title = {Python-based Open Source Package for Optimization of Contact-rich Systems},
- booktitle = {Robotics: Science and Systems},
- year = 2022,
- month = jun,
- url = {https://www.merl.com/publications/TR2022-089}
- }
- , "Robust Pivoting Manipulation Using Bilevel Contact-Implicit Optimization", RSS Workshop on The Science of Bumping into Things, June 2022.BibTeX TR2022-090 PDF
- @inproceedings{Shirai2022jun,
- author = {Shirai, Yuki and Jha, Devesh K. and Raghunathan, Arvind and Romeres, Diego},
- title = {Robust Pivoting Manipulation Using Bilevel Contact-Implicit Optimization},
- booktitle = {RSS Workshop on The Science of Bumping into Things},
- year = 2022,
- month = jun,
- url = {https://www.merl.com/publications/TR2022-090}
- }
- , "Auto-Tuning of Controller and Online Trajectory Planner for Legged Robots", IEEE Robotics and Automation Letters, DOI: 10.1109/LRA.2022.3185387, Vol. 7, No. 3, pp. 7802-7809, June 2022.BibTeX TR2022-085 PDF
- @article{Schperberg2022jun,
- author = {Schperberg, Alexander and Di Cairano, Stefano and Menner, Marcel},
- title = {Auto-Tuning of Controller and Online Trajectory Planner for Legged Robots},
- journal = {IEEE Robotics and Automation Letters},
- year = 2022,
- volume = 7,
- number = 3,
- pages = {7802--7809},
- month = jun,
- doi = {10.1109/LRA.2022.3185387},
- url = {https://www.merl.com/publications/TR2022-085}
- }
- , "1 Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application", IEEE Transaction on Robotics, December 2022.
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Videos
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Robot Locomotion by Automated Controller Tuning
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Real-time Mixed-integer Programming for Vehicle Decision Making and Motion Planning
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[MERL Seminar Series Spring 2022] Hybrid robotics and implicit learning
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[MERL Seminar Series Spring 2022] Exact Structural Analysis of Multimode Modelica Models
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[MERL Seminar Series Spring 2022] Self-Supervised Scene Representation Learning
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[MERL Seminar Series 2021] Learning to See by Moving: Self-supervising 3D scene representations for perception, control, and visual reasoning
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Robotic Research at MERL
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Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models
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Modelica-Based Modeling and Control of a Delta Robot
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Towards Human-Level Learning of Complex Physical Puzzles
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Assembly of Belt Drive Units
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Examples of Robotic Manipulation
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Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry
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Cooperating Modular Goal Selection and Motion Planning for Autonomous Driving
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Deep Reactive Planning in Dynamic Environments
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Monte Carlo Probabilistic Inference for Learning Control
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Experimental Validation of Reachability-based Decision Making for Autonomous Driving
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Software Downloads
