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
Tim K.
Marks
Karl
Berntorp
Scott A.
Bortoff
Radu
Corcodel
Siddarth
Jain
Kei
Ota
Ye
Wang
Matthew
Brand
Rien
Quirynen
Bingnan
Wang
Avishai
Weiss
Anoop
Cherian
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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TALK Prof. Kevin Lynch presents talk titled Autonomous and Human-Collaborative Robotic Manipulation Date & Time: Tuesday, February 28, 2023; 12:00 PM
Speaker: Prof. Kevin Lynch, Northwestern University
MERL Host: Diego Romeres
Research Areas: Machine Learning, RoboticsAbstract- Research at the Center for Robotics and Biosystems at Northwestern University includes bio-inspiration, neuromechanics, human-machine systems, and swarm robotics, among other topics. In this talk I will focus on our work on manipulation, including autonomous in-hand robotic manipulation and safe, intuitive human-collaborative manipulation among one or more humans and a team of mobile manipulators.
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NEWS Rien Quirynen Appointed IPC Vice-Chair for the 8th IFAC Conference on NMPC 2024 Date: August 27, 2024 - August 30, 2024
Where: Kyoto, Japan
MERL Contact: Rien Quirynen
Research Areas: Control, Machine Learning, Multi-Physical Modeling, Optimization, RoboticsBrief- MERL researcher Rien Quirynen has been appointed as Vice-Chair from Industry of the International Program Committee of the 8th IFAC Conference on Nonlinear Model Predictive Control, which will be held in Kyoto, Japan, in August 2024.
IFAC NMPC is the main symposium focused on model predictive control, theory, methods and applications, includes contributions on control, optimization, and machine learning research, and is held every 3 years.
- MERL researcher Rien Quirynen has been appointed as Vice-Chair from Industry of the International Program Committee of the 8th IFAC Conference on Nonlinear Model Predictive Control, which will be held in Kyoto, Japan, in August 2024.
See All News & Events for Robotics -
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Internships
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CV1992: High precision pose estimation of deformable objects
MERL is seeking a highly motivated intern to conduct original research in high precision pose estimation of deformable objects. Applicants are required to have a strong background in image processing, machine vision and point cloud processing using depth cameras. The internship is open to PhD students, preferably specializing in Computer Vision, with a strong publication record, solid programming skills in Python and/or C/C++, and preferably some experience using tactile sensors. Internship duration and start date are flexible.
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MS2005: Modeling and Control of Robotic Contacts and Collisions
MERL is seeking a highly motivated and qualified intern to conduct research into
hybrid modeling and control of object contact and collision for precise robotic assembly.
The ideal candidate is expected to be working toward a Ph.D. or equivalent degree
in the area of modeling and control of hybrid systems (those with both continuous and
discrete states), with strong knowledge and interest in differential algebraic
equations (DAEs), nonlinear and hybrid control theory, geometric algebra
and coordinate-free geometric methods. The research involves formalizing and extending
a hybrid DAE-based method of modeling the physics of object contact and collision to
include acausal effects of friction, address contact constraints of dimension
greater then one among objects, and formalize the method using hybrid systems theory
to study well-posedness issues and enable application of optimal control theory for
path planning and control of robotic assembly problems. The expected start of of the
internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months. -
CA1904: Numerical Optimal Control for Hybrid Dynamical Systems
MERL is looking for a highly motivated individual to work on tailored computational algorithms for numerical optimal control of hybrid dynamical systems and applications for decision making, motion planning and control of autonomous systems. The research will involve the study and development of numerical optimal control methods for systems with continuous dynamics and discrete logic, nonsmooth and/or switched dynamics, and the implementation and validation of such algorithms for industrial applications, e.g., related to autonomous driving and robotics. The ideal candidate should have experience in either one or multiple of the following topics: mixed-integer programming (MIP), mathematical programs with complementarity constraints (MPCCs), modeling and formulation of optimal control problems for hybrid dynamical systems, convex and non-convex optimization, machine learning and real-time optimization. PhD students in engineering or mathematics, especially with a focus on MIPs, MPCCs or numerical optimal control, are encouraged to apply. Publication of relevant results in conference proceedings or journals is expected. Capability of implementing the designs and algorithms in MATLAB/Python is expected; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is 3-6 months and the start date is flexible.
See All Internships for Robotics -
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Recent Publications
- "H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions", IEEE International Conference on Robotics and Automation (ICRA), March 2023.BibTeX TR2023-009 PDF
- @inproceedings{Ota2023mar,
- author = {Ota, Kei and Tung, Hsiao-Yu and Smith, Kevin and Cherian, Anoop and Marks, Tim K. and Sullivan, Alan and Kanezaki, Asako and Tenenbaum, Joshua B.},
- title = {H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2023,
- month = mar,
- url = {https://www.merl.com/publications/TR2023-009}
- }
, - "Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application", IEEE Transaction on Robotics, DOI: 10.1109/TRO.2022.3184837, Vol. 38, No. 6, pp. 3879-3898, 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 = {Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application},
- journal = {IEEE Transaction on Robotics},
- year = 2022,
- volume = 38,
- number = 6,
- pages = {3879--3898},
- month = dec,
- doi = {10.1109/TRO.2022.3184837},
- issn = {1941-0468},
- url = {https://www.merl.com/publications/TR2022-154}
- }
, - "Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC51059.2022.9992979, December 2022, pp. 7571-7578.BibTeX TR2022-157 PDF
- @inproceedings{Raghunathan2022dec,
- author = {Raghunathan, Arvind and Jha, Devesh K. and Romeres, Diego},
- title = {Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs},
- booktitle = {IEEE 61st Conference on Decision and Control (CDC), Cancun, Mexico},
- year = 2022,
- pages = {7571--7578},
- month = dec,
- doi = {10.1109/CDC51059.2022.9992979},
- url = {https://www.merl.com/publications/TR2022-157}
- }
, - "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), DOI: 10.1109/CCTA49430.2022.9966181, August 2022, pp. 676-682.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,
- pages = {676--682},
- month = aug,
- publisher = {IEEE},
- doi = {10.1109/CCTA49430.2022.9966181},
- 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}
- }
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- "H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions", IEEE International Conference on Robotics and Automation (ICRA), March 2023.
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Videos
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Simultaneous Tactile Estimation and Control of Extrinsic Contact
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Robust Pivoting Manipulation using Contact Implicit Bilevel Optimization
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Tactile-Filter: Interactive Tactile Perception for Part Mating
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Tactile tool manipulation
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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