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
Yebin
Wang
William S.
Yerazunis
Karl
Berntorp
Mouhacine
Benosman
Radu
Corcodel
Toshiaki
Koike-Akino
Tim K.
Marks
Scott A.
Bortoff
Abraham P.
Vinod
Avishai
Weiss
Rien
Quirynen
Ye
Wang
Matthew
Brand
Marcus
Greiff
Jonathan
Le Roux
Philip V.
Orlik
Bingnan
Wang
Anoop
Cherian
Abraham
Goldsmith
Jianlin
Guo
Chiori
Hori
Hassan
Mansour
Koon Hoo
Teo
Anthony
Vetro
Pedro
Miraldo
James
Queeney
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Awards
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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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AWARD Marcus Greiff receives Outstanding Student Paper Award at CCTA 2022 Date: August 25, 2022
Awarded to: Marcus Greiff
MERL Contact: Marcus Greiff
Research Areas: Control, Dynamical Systems, RoboticsBrief- 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.
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News & Events
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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.
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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, RoboticsAbstract
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.
See All News & Events for Robotics -
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Internships
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CA2131: Collaborative Legged Robots
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on control and planning algorithms for legged robots for support activities of and collaboration with humans. The ideal candidate is expected to be working towards a PhD with strong emphasis in robotics control and planning and to have interest and background in as many as possible of: motion planning algorithms, control for legged robot locomotions, legged robots, perception and sensing with multiple sensors, SLAM, vision-based control. Good programming skills in Python or C/C++ are required. The expected start of of the internship is flexible, with duration of 3--6 months.
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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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OR2116: Collaborative robotic manipulation
MERL is offering a new research internship opportunity in the field of robotic manipulation. The position requires a robotics background, excellent programming skills and experience with Deep RL and Computer Vision. 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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Openings
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Recent Publications
- , "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), October 2023.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,
- month = oct,
- 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), September 2023.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,
- month = sep,
- 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}
- }
- , "Athletic Intelligence Olympics challenge with Model-Based Reinforcement Learning", International Joint Conference on Artificial Intelligence, August 2023.BibTeX TR2023-111 PDF
- @inproceedings{DallaLibera2023aug,
- author = {Dalla Libera, Alberto and Turcato, Niccolò and Giacomuzzo, Giulio and Carli, Ruggero and Romeres, Diego},
- title = {Athletic Intelligence Olympics challenge with Model-Based Reinforcement Learning},
- booktitle = {International Joint Conference on Artificial Intelligence},
- year = 2023,
- month = aug,
- url = {https://www.merl.com/publications/TR2023-111}
- }
- , "Trajectory Generation for Online Payload Estimation of Robot Manipulators: A Supervised Learning Based Approach", IEEE Conference on Automation and Science Engineering, DOI: 10.1109/CASE56687.2023.10260415, August 2023.BibTeX TR2023-106 PDF
- @inproceedings{Duan2023aug,
- author = {Duan, Xiaoming and Wang, Yebin and Romeres, Diego and Koike-Akino, Toshiaki and Orlik, Philip V.},
- title = {Trajectory Generation for Online Payload Estimation of Robot Manipulators: A Supervised Learning Based Approach},
- booktitle = {IEEE Conference on Automation and Science Engineering},
- year = 2023,
- month = aug,
- doi = {10.1109/CASE56687.2023.10260415},
- isbn = {979-8-3503-2070-1},
- url = {https://www.merl.com/publications/TR2023-106}
- }
- , "Style-transfer based Speech and Audio-visual Scene understanding for Robot Action Sequence Acquisition from Videos", Interspeech, DOI: 10.21437/Interspeech.2023-1983, August 2023, pp. 4663-4667.BibTeX TR2023-104 PDF
- @inproceedings{Hori2023aug,
- author = {Hori, Chiori and Peng, Puyuang and Harwath, David and Liu, Xinyu and Ota, Kei and Jain, Siddarth and Corcodel, Radu and Jha, Devesh K. and Romeres, Diego and Le Roux, Jonathan},
- title = {Style-transfer based Speech and Audio-visual Scene understanding for Robot Action Sequence Acquisition from Videos},
- booktitle = {Interspeech},
- year = 2023,
- pages = {4663--4667},
- month = aug,
- doi = {10.21437/Interspeech.2023-1983},
- url = {https://www.merl.com/publications/TR2023-104}
- }
- , "Motion Planning of Articulated Vehicles with Active Trailer Steering by Particle Filtering", Conference on Control Technology and Applications (CCTA), DOI: 10.1109/CCTA54093.2023.10253020, August 2023.BibTeX TR2023-101 PDF
- @inproceedings{Iqbal2023aug,
- author = {Iqbal, Hassan and Di Cairano, Stefano and Berntorp, Karl},
- title = {Motion Planning of Articulated Vehicles with Active Trailer Steering by Particle Filtering},
- booktitle = {Conference on Control Technology and Applications (CCTA)},
- year = 2023,
- month = aug,
- doi = {10.1109/CCTA54093.2023.10253020},
- url = {https://www.merl.com/publications/TR2023-101}
- }
- , "Physics Informed Gaussian Process Regression Methods for Robot Inverse Dynamics Identification", Conferenza Italiana di Robotica e Macchine Intelligenti, October 2023.
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Videos
[MERL Seminar Series Fall 2023] The Confluence of Vision, Language, and Robotics [MERL Seminar Series Fall 2023] Composable Optimization for Robotic Simulation, Planning, and Control Simultaneous Trajectory Optimization and Contact Selection for Multi-Modal Manipulation Planning A Virtual Reality Teleoperation Interface for Industrial Robot Manipulators Simultaneous Tactile Estimation and Control of Extrinsic Contact Robust Pivoting Manipulation using Contact Implicit Bilevel Optimization Tactile-Filter: Interactive Tactile Perception for Part Mating [MERL Seminar Series Spring 2023] Towards Complex Language in Partially Observed Environments Tactile tool manipulation Robot Locomotion by Automated Controller Tuning Real-time Mixed-integer Programming for Vehicle Decision Making and Motion Planning [MERL Seminar Series Spring 2022] Hybrid robotics and implicit learning [MERL Seminar Series Spring 2022] Exact Structural Analysis of Multimode Modelica Models [MERL Seminar Series Spring 2022] Self-Supervised Scene Representation Learning [MERL Seminar Series 2021] Learning to See by Moving: Self-supervising 3D scene representations for perception, control, and visual reasoning Robotic Research at MERL Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models Modelica-Based Modeling and Control of a Delta Robot Towards Human-Level Learning of Complex Physical Puzzles Assembly of Belt Drive Units Examples of Robotic Manipulation Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry Cooperating Modular Goal Selection and Motion Planning for Autonomous Driving Deep Reactive Planning in Dynamic Environments Monte Carlo Probabilistic Inference for Learning Control Experimental Validation of Reachability-based Decision Making for Autonomous Driving
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Software & Data Downloads
