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
Siddarth
Jain
William S.
Yerazunis
Yebin
Wang
Karl
Berntorp
Radu
Corcodel
Mouhacine
Benosman
Toshiaki
Koike-Akino
Tim K.
Marks
Scott A.
Bortoff
Abraham P.
Vinod
Avishai
Weiss
Ye
Wang
Matthew
Brand
Chiori
Hori
Jonathan
Le Roux
Philip V.
Orlik
Bingnan
Wang
Anoop
Cherian
Abraham
Goldsmith
Jianlin
Guo
Hassan
Mansour
Koon Hoo
Teo
Anthony
Vetro
Pedro
Miraldo
James
Queeney
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Awards
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AWARD Honorable Mention Award at NeurIPS 23 Instruction Workshop Date: December 15, 2023
Awarded to: Lingfeng Sun, Devesh K. Jha, Chiori Hori, Siddharth Jain, Radu Corcodel, Xinghao Zhu, Masayoshi Tomizuka and Diego Romeres
MERL Contacts: Radu Corcodel; Chiori Hori; Siddarth Jain; Devesh K. Jha; Diego Romeres
Research Areas: Artificial Intelligence, Machine Learning, RoboticsBrief- MERL Researchers received an "Honorable Mention award" at the Workshop on Instruction Tuning and Instruction Following at the NeurIPS 2023 conference in New Orleans. The workshop was on the topic of instruction tuning and Instruction following for Large Language Models (LLMs). MERL researchers presented their work on interactive planning using LLMs for partially observable robotic tasks during the oral presentation session at the workshop.
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AWARD Joint University of Padua-MERL team wins Challenge 'AI Olympics With RealAIGym' Date: August 25, 2023
Awarded to: Alberto Dalla Libera, Niccolo' Turcato, Giulio Giacomuzzo, Ruggero Carli, Diego Romeres
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Machine Learning, RoboticsBrief- A joint team consisting of members of University of Padua and MERL ranked 1st in the IJCAI2023 Challenge "Al Olympics With RealAlGym: Is Al Ready for Athletic Intelligence in the Real World?". The team was composed by MERL researcher Diego Romeres and a team from University Padua (UniPD) consisting of Alberto Dalla Libera, Ph.D., Ph.D. Candidates: Niccolò Turcato, Giulio Giacomuzzo and Prof. Ruggero Carli from University of Padua.
The International Joint Conference on Artificial Intelligence (IJCAI) is a premier gathering for AI researchers and organizes several competitions. This year the competition CC7 "AI Olympics With RealAIGym: Is AI Ready for Athletic Intelligence in the Real World?" consisted of two stages: simulation and real-robot experiments on two under-actuated robotic systems. The two robotics systems were treated as separate tracks and one final winner was selected for each track based on specific performance criteria in the control tasks.
The UniPD-MERL team competed and won in both tracks. The team's system made strong use of a Model-based Reinforcement Learning algorithm called (MC-PILCO) that we recently published in the journal IEEE Transaction on Robotics.
- A joint team consisting of members of University of Padua and MERL ranked 1st in the IJCAI2023 Challenge "Al Olympics With RealAlGym: Is Al Ready for Athletic Intelligence in the Real World?". The team was composed by MERL researcher Diego Romeres and a team from University Padua (UniPD) consisting of Alberto Dalla Libera, Ph.D., Ph.D. Candidates: Niccolò Turcato, Giulio Giacomuzzo and Prof. Ruggero Carli from University of Padua.
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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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News & Events
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EVENT MERL Contributes to ICASSP 2024 Date: Sunday, April 14, 2024 - Friday, April 19, 2024
Location: Seoul, South Korea
MERL Contacts: Petros T. Boufounos; François Germain; Chiori Hori; Sameer Khurana; Toshiaki Koike-Akino; Jonathan Le Roux; Hassan Mansour; Zexu Pan; Kieran Parsons; Joshua Rapp; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern; Ryoma Yataka
Research Areas: Artificial Intelligence, Computational Sensing, Machine Learning, Robotics, Signal Processing, Speech & AudioBrief- MERL has made numerous contributions to both the organization and technical program of ICASSP 2024, which is being held in Seoul, Korea from April 14-19, 2024.
Sponsorship and Awards
MERL is proud to be a Bronze Patron of the conference and will participate in the student job fair on Thursday, April 18. Please join this session to learn more about employment opportunities at MERL, including openings for research scientists, post-docs, and interns.
MERL is pleased to be the sponsor of two IEEE Awards that will be presented at the conference. We congratulate Prof. Stéphane G. Mallat, the recipient of the 2024 IEEE Fourier Award for Signal Processing, and Prof. Keiichi Tokuda, the recipient of the 2024 IEEE James L. Flanagan Speech and Audio Processing Award.
Jonathan Le Roux, MERL Speech and Audio Senior Team Leader, will also be recognized during the Awards Ceremony for his recent elevation to IEEE Fellow.
Technical Program
MERL will present 13 papers in the main conference on a wide range of topics including automated audio captioning, speech separation, audio generative models, speech and sound synthesis, spatial audio reproduction, multimodal indoor monitoring, radar imaging, depth estimation, physics-informed machine learning, and integrated sensing and communications (ISAC). Three workshop papers have also been accepted for presentation on audio-visual speaker diarization, music source separation, and music generative models.
Perry Wang is the co-organizer of the Workshop on Signal Processing and Machine Learning Advances in Automotive Radars (SPLAR), held on Sunday, April 14. It features keynote talks from leaders in both academia and industry, peer-reviewed workshop papers, and lightning talks from ICASSP regular tracks on signal processing and machine learning for automotive radar and, more generally, radar perception.
Gordon Wichern will present an invited keynote talk on analyzing and interpreting audio deep learning models at the Workshop on Explainable Machine Learning for Speech and Audio (XAI-SA), held on Monday, April 15. He will also appear in a panel discussion on interpretable audio AI at the workshop.
Perry Wang also co-organizes a two-part special session on Next-Generation Wi-Fi Sensing (SS-L9 and SS-L13) which will be held on Thursday afternoon, April 18. The special session includes papers on PHY-layer oriented signal processing and data-driven deep learning advances, and supports upcoming 802.11bf WLAN Sensing Standardization activities.
Petros Boufounos is participating as a mentor in ICASSP’s Micro-Mentoring Experience Program (MiME).
About ICASSP
ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 3000 participants.
- MERL has made numerous contributions to both the organization and technical program of ICASSP 2024, which is being held in Seoul, Korea from April 14-19, 2024.
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NEWS Invited talk given by Diego Romeres at Bentley University Date: November 1, 2023
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Machine Learning, RoboticsBrief- Principal Research Scientist and Team Leader Diego Romeres gave an invited talk with title 'Applications of Machine Learning to Robotics' in the Machine Learning graduate course at Bentley University. The presentation focused mainly on Reinforcement Learning research applied to robotics. The audience consisted mostly of Master’s in Business Analytics (MSBA) students and students in the MBA w/ Business Analytics Concentration program.
See All News & Events for Robotics -
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Internships
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CA1940: Autonomous vehicle planning and contro in uncertain environments
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on planning and control for autonomous vehicles in uncertain surrounding environments. The research domain includes algorithms for path planning and control in environments that are uncertain and perceived by sensing and predicted according to models and data. The ideal candidate is expected to be working towards a PhD with strong emphasis in vehicle guidance and control, and to have interest and background in as many as possible of: vehicle dynamics modeling and control, sensor uncertainty modeling, data-driven prediction, predictive control for uncertain systems, motion planning. Good programming skills in MATLAB, Python are required, knowledge of C/C++, rapid prototyping systems, automatic code generation, vehicle simulation packages (CarSim, CarMaker) or ROS are a plus. The expected start of of the internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months.
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OR2103: Human Robot Collaboration in Assembly Tasks
MERL is looking for a self-motivated and qualified candidate to work on human-robot-interaction for manipulation and assembly collaborative scenarios. The ideal candidate is a PhD student and should have experience and records in one or multiple of the following areas. 1) Control, estimation and perception for Robotic manipulation 2) Task and Motion Planning 3) Learning from demonstration algorithms applied to robotic manipulation 4) Machine learning techniques for modeling and control as well as regression and classification problems. 5) Experience in working with robotic systems and familiarity with physics engine simulators like Mujoco, Isaac Gym, PyBullet. The successful candidate will be expected to develop, in collaboration with MERL employees, state of the art algorithms to solve complex manipulation tasks that involve human and robot collaborations. Proficiency in Python and ROS are required. The expectation is that the research will lead to one or more scientific publications. The expected duration s 3-4 months, with a flexible starting date.
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OR2110: Shared Autonomy for Human-Robot Interaction
MERL is looking for a highly motivated and qualified intern to work on human-robot interaction (HRI) research. The ideal candidate would be a Ph.D. student with a strong background in HRI, focusing on robotic manipulation, deep learning, probabilistic modeling, or reinforcement learning. Several topics are available for consideration, including Intent Recognition in Multi-Object Scenes, Shared Autonomy, Cooperative Manipulation, Human-Robot Handovers, and Representation Learning for HRI. Experience working with robotics hardware and physics engine simulators like PyBullet, Issac Gym, or Mujoco is preferred. Proficiency in Python programming is necessary, and experience with ROS is a plus. The successful candidate will collaborate with MERL researchers, and publication of the relevant results is expected. The start date is flexible, and the expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their recent CV and list of publications in related topics.
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Recent Publications
- "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}
- }
, - "Stochastic Learning Manipulation of Object Pose With Under-Actuated Impulse Generator Arrays", International Conference on Machine Learning and Applications (ICMLA), DOI: 10.1109/ICMLA58977.2023.00024, December 2023, pp. 112-119.BibTeX TR2023-151 PDF
- @inproceedings{Kong2023dec,
- author = {Kong, Chuizheng and Yerazunis, William S. and Nikovski, Daniel},
- title = {Stochastic Learning Manipulation of Object Pose With Under-Actuated Impulse Generator Arrays},
- booktitle = {International Conference on Machine Learning and Applications (ICMLA)},
- year = 2023,
- pages = {112--119},
- month = dec,
- doi = {10.1109/ICMLA58977.2023.00024},
- url = {https://www.merl.com/publications/TR2023-151}
- }
, - "Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks", Advances in Neural Information Processing Systems (NeurIPS) Workshop on Instruction Tuning and Instruction Following, December 2023.BibTeX TR2023-148 PDF
- @inproceedings{Sun2023dec,
- author = {Sun, Lingfeng and Jha, Devesh K. and Hori, Chiori and Jain, Siddarth and Corcodel, Radu and Zhu, Xinghao and Tomizuka, Masayoshi and Romeres, Diego},
- title = {Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS) Workshop on Instruction Tuning and Instruction Following},
- year = 2023,
- month = dec,
- url = {https://www.merl.com/publications/TR2023-148}
- }
, - "Physics Informed Gaussian Process Regression Methods for Robot Inverse Dynamics Identification", Conferenza Italiana di Robotica e Macchine Intelligenti, October 2023.BibTeX TR2023-132 PDF
- @inproceedings{Giacomuzzo2023oct2,
- author = {Giacomuzzo, Giulio and Dalla Libera, Alberto and Romeres, Diego and Carli, Ruggero},
- title = {Physics Informed Gaussian Process Regression Methods for Robot Inverse Dynamics Identification},
- booktitle = {Conferenza Italiana di Robotica e Macchine Intelligenti},
- year = 2023,
- month = oct,
- url = {https://www.merl.com/publications/TR2023-132}
- }
, - "EARL: Eye-on-Hand Reinforcement Learner for Dynamic Grasping with Active Pose Estimation", 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), DOI: 10.1109/IROS55552.2023.10341988, October 2023, pp. 2963-2970.BibTeX TR2023-118 PDF Video
- @inproceedings{Huang2023oct,
- author = {Huang, Baichuan and Yu, Jingjin and Jain, Siddarth},
- title = {EARL: Eye-on-Hand Reinforcement Learner for Dynamic Grasping with Active Pose Estimation},
- booktitle = {2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2023,
- pages = {2963--2970},
- month = oct,
- publisher = {IEEE},
- doi = {10.1109/IROS55552.2023.10341988},
- issn = {2153-0866},
- isbn = {978-1-6654-9190-7},
- url = {https://www.merl.com/publications/TR2023-118}
- }
, - "Constrained Dynamic Movement Primitives for Collision Avoidance in Novel Environments", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), DOI: 10.1109/IROS55552.2023.10341839, September 2023, pp. 3672-3679.BibTeX TR2023-121 PDF Video
- @inproceedings{Shaw2023sep,
- author = {Shaw, Seiji and Jha, Devesh K. and Raghunathan, Arvind and Corcodel, Radu and Romeres, Diego and Konidaris, George and Nikovski, Daniel},
- title = {Constrained Dynamic Movement Primitives for Collision Avoidance in Novel Environments},
- booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2023,
- pages = {3672--3679},
- month = sep,
- publisher = {IEEE},
- doi = {10.1109/IROS55552.2023.10341839},
- issn = {2153-0866},
- isbn = {978-1-6654-9190-7},
- url = {https://www.merl.com/publications/TR2023-121}
- }
, - "Contact-Aware Covariance Control of Stochastic Contact-Rich Systems", IROS 2023 Workshop on Leveraging Models for Contact-Rich Manipulation, September 2023.BibTeX TR2023-120 PDF
- @inproceedings{Shirai2023sep,
- author = {Shirai, Yuki and Jha, Devesh K. and Raghunathan, Arvind},
- title = {Contact-Aware Covariance Control of Stochastic Contact-Rich Systems},
- booktitle = {IROS 2023 Workshop on Leveraging Models for Contact-Rich Manipulation},
- year = 2023,
- month = sep,
- url = {https://www.merl.com/publications/TR2023-120}
- }
, - "Estimation of Extrinsic Contact Patch for Stable Placement", IEEE IROS 2023 Workshop on Visuo-Tactile Perception, Learning, Control for Manipulation and HRI, September 2023.BibTeX TR2024-018 PDF
- @inproceedings{Ota2023sep2,
- author = {Ota, Kei and Jha, Devesh K. and Jatavallabhula, Krishna and Kanezaki, Asako and Tenenbaum, Joshua B.},
- title = {Estimation of Extrinsic Contact Patch for Stable Placement},
- booktitle = {IEEE IROS 2023 Workshop on Visuo-Tactile Perception, Learning, Control for Manipulation and HRI},
- year = 2023,
- month = sep,
- url = {https://www.merl.com/publications/TR2024-018}
- }
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- "Chance-Constrained Optimization for Contact-rich Systems using Mixed Integer Programming", Nonlinear Analysis: Hybrid Systems, December 2024.
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Videos
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Software & Data Downloads