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Brenna ArgallAssociate Professor of Computer ScienceAssociate Professor of Mechanical EngineeringAssociate Professor of Physical Medicine and Rehabilitation

About Brenna Argall

Dr. Argall is an associate professor of Mechanical Engineering, Computer Science, and Physical Medicine & Rehabilitation at Northwestern University. Her research lies at the intersection of robotics autonomy, machine learning and human rehabilitation. She is director of the assistive & rehabilitation robotics laboratory (argallab) at the Shirley Ryan AbilityLab, the nation’s premier rehabilitation hospital. The mission of the argallab is to advance human ability by leveraging robotics autonomy.

Argall is a 2016 recipient of the NSF CAREER award, and was named one of the 40 under 40 by Crain’s Chicago Business. Her Ph.D. in Robotics (2009) was received from the Robotics Institute at Carnegie Mellon University, where she was a member of the CORAL Research Group. Her B.S. in Mathematics (2002) also was received from Carnegie Mellon, where she minored in Music and Biological Sciences. Prior to joining Northwestern and RIC, she was a postdoctoral fellow (2009-2011) in the Learning Algorithms and Systems Laboratory at the École Polytechnique Fédérale de Lausanne (EPFL). Prior to graduate school she held a Computational Biology position in the Laboratory of Brain & Cognition at the National Institutes of Health (NIH).

About Argallab

The Assistive and Rehabilitation Robotics Laboratory (argallab) strives to advance human ability by leveraging robotics autonomy. I am the founder and director of the argallab, which is located at the Rehabilitation Institute of Chicago.

It is an irony that often the more severe a person’s motor impairment, the more challenging it is for them to operate the very assistive machines which might enhance their quality of life. A primary aim of the argallab is to address this confound by incorporating robotics autonomy and intelligence into assistive machines—turning the machine into a kind of robot, and offloading some of the control burden from the user to the machine.

Our lab strives to advance human ability through robotics autonomy—by easing the burden of operating assistive machines. Our lab’s research lies at the intersection of artificial intelligence, rehabilitation robotics and machine learning. By easing the control burden of assistive machines, the argallab strives to advance human ability through robotics autonomy.

A distinguishing theme present within many of our projects is that the machine automation is customizable—to a user’s physical abilities, personal preferences or even financial means. A fundamental question that arises time and again throughout many of our projects is how exactly to share control between the robot and the human user.

We are working with a range of hardware platforms, from smart wheelchairs to assistive robotic arms. Watch this video to learn what we are about and watch a seminar about our work. 

Learn about open positions within my research group.

 

ECE 495: Machine Learning & Artificial Intelligence for Robotics. 

Introductory Robotics Laboratory.  View the course website.

Argall is also a faculty advisor for the Masters of Science in Robotics program.

Ph.D. Robotics, Carnegie Mellon University (2009)

M.S.  Robotics, Carnegie Mellon University (2006)

B.S.  Mathematics, Carnegie Mellon University (2002)

S. Jain and B. Argall. Probabilistic Human Intent Recognition for Shared Autonomy in Assistive Robotics. Accepted for publication in Transactions on Human-Robot Interaction.

M. Young, M. Nejati and B. Argall. Discrete N-Dimensional Entropy of Behavior: DNDEB. To appear in Proceedings of the IEEE International Conference on Intelligent Robots (IROS), Macao, China, Oct. 2019.

M. Nejati, M. Young and B. Argall. Interface Operation and Implications for Shared-Control Assistive Robots. In Proceedings of the IEEE-RAS-EMBS International Conference on Rehabilitation Robotics (ICORR), Toronto, Canada, June 2019. *Finalist for Best Student Paper Award.

A. Broad, T. Murphey and B. Argall. Highly Parallelized Data-driven MPC for Minimal Intervention Shared Control. In Proceedings of Robotics: Science and Systems (RSS), Freiburg, Germany, Jun. 2019.

M. Young, C. Miller, Y. Bi, W. Chen, and B. D. Argall. Formalized Task Characterization for Human-Robot Autonomy Allocation. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.

A. Broad, T. Murphey and B. Argall. Operation and Imitation under Safety-Aware Shared Control. In Proceedings of the Workshop on the Algorithmic Foundations of Robotics (WAFR), Mérida, México, December, 2018.

S. Jain and B. Argall. Recursive Bayesian Intent Inference in Shared-Control Robotics. In Proceedings of the IEEE International Conference on Intelligent Robots (IROS), Madrid, Spain, Oct. 2018.

B. D. Argall. Autonomy in Rehabilitation Robotics: An Intersection. Annual Review of Control, Robotics, and Autonomous Systems, 1, 441-463, 2018.

M. Young, M. Nejati, A. Erdogan and B. Argall. An Analysis of Degraded Communication Channels in Human-Robot Teaming and Implications for Dynamic Autonomy Allocation. In Proceedings of the Conference on Field and Service Robotics (FSR), Zurich, Switzerland, September 2017.

A. Erdogan and B. Argall. The Effect Robotic Wheelchair Control Paradigm and Interface on User Performance, Effort and Preference: An Experimental Assessment. Robotics and Autonomous Systems, 94, 282-297, 2017.

A. Broad, T. Murphey and B. Argall. Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics. In Proceedings of Robotics: Science and Systems (RSS), Boston, Massachusetts, USA, July 2017.

D. Gopinath and B. Argall. Mode Switch Assistance To Maximize Human Intent Disambiguation. In Proceedings of Robotics: Science and Systems (RSS), Boston, Massachusetts, USA, July 2017.

A. Erdogan and B. Argall. Prediction of User Preference over Shared-Control Paradigms for a Robotic Wheelchair. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), London, United Kingdom, July 2017.

A. Broad, J. Arkin, N. Ratliff, T. Howard and B. Argall. Real-Time Natural Language Corrections for Assistive Manipulation Tasks. International Journal of Robotics Research, 36(5-7), 684-698, 2017.

P. Beckerle, G. Salvietti, R. Ünal, D. Prattichizzo, S. Rossi, C. Castellini, S. Hirche, S. Endo, H. Ben Amor, M. Ciocarlie, F. Mastrogiovanni, B. D. Argall and M. Bianchi. A Human-Robot Interaction Perspective on Assistive and Rehabilitation Robotics. Frontiers in Neurorobotics, 2017.

S. Mohammed, H. W. Park, C. H. Park, Y. Amirat and B. Argall. Special Issue on Assistive and Rehabilitation Robotics. Autonomous Robots, 41(3), 513-517, 2017

A. Broad, M. Derry, J. Schultz, T. Murphey and B. Argall. Trust Adaptation Leads to Lower Control Effort in Shared Control of Crane Automation. IEEE Robotics and Automation Letters 2(1), 239-246, 2017. (Also presented at the Conference on Automation Science and Engineering (CASE), Fort Worth, Texas, USA, August 2016.)

D. Gopinath, S. Jain and B. Argall. Human-in-the-Loop Optimization of Shared Autonomy in Assistive Robotics. IEEE Robotics and Automation Letters, 2(1), 247-254, 2017. (Also presented at the Conference on Automation Science and Engineering (CASE), Fort Worth, Texas, USA, August 2016.)

M. Nejati and B. Argall. Automated Incline and Drop-off Detection for Assistive Powered Wheelchairs. In Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), New York, New York, USA, August 2016.

D. Gopinath, P. Egli and B. Argall. A Call for Convergence of Research Directions in Assistive Robotics. In RSS Workshop on Socially and Physically Assistive Robotics for Humanity, Ann Arbor, Michigan, USA, June 2016.

A. Broad and B. Argall. Path Planning under Kinematic Constraints for Shared Human-Robot Control. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), London, United Kingdom, June 2016.

S. Jain and B. Argall. Grasp Detection for Assistive Robotic Manipulation. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016.

S. Jain and B. Argall. Online and User Centric Customization of Shared Autonomy for Intelligent Assistive Devices. In ICRA 2016 Workshop on Human-Robot Interfaces for Enhanced Physical Interactions, May 2016.

S. Jain, K. Barsness and B. Argall. Automated and Objective Assessment of Surgical Training: Detection of Procedural Steps on Videotaped Performances. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), Adelaide, Australia, November 2015.

S. Jain, A. Farshchiansadegh, A. Broad, F. Abdollahi, F. Mussa-Ivaldi and B. Argall. Assistive Robotic Manipulation through Shared Autonomy and a Body-Machine Interface. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), Singapore, August 2015.

B. D. Argall. Information Extraction under Communication Constraints within Assistive Robot Domains. In RSS Workshop on Model Learning for Human­Robot Communication, Rome, Italy, July 2015.

B. Argall. Turning Assistive Machines into Assistive Robots. In Proceedings of SPIE 9370, Quantum Sensing and Nanophotonic Devices XII, San Francisco, California, USA, February 2015. (Keynote paper)

B. D. Argall and T. M. Murphey. Computable Trust in Human Instruction. In Proceedings of the AAAI Fall Symposium on Artificial Intelligence for Human-­Robot Interaction, Arlington, Virginia, USA, November 2014.

M. Derry and B. Argall. A Probabilistic Representation of User Intent for Assistive Robots. In IROS Workshop on Rehabilitation and Assistive Robotics, Chicago, Illinois, USA, September 2014.

T. D. Murphey and B. D. Argall. Towards Software-Enabled Rehabilitation. In IROS Workshop on Rehabilitation and Assistive Robotics, Chicago, Illinois, USA, September 2014.

S. Jain and B. Argall. Automated Perception of Safe Docking Locations with Alignment Information for Assistive Wheelchairs. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, Illinois, USA, September 2014.

B. D. Argall. Modular and Adaptive Wheelchair Automation. In Proceedings of the International Symposium on Experimental Robotics (ISER), Marrakech, Morrocco, June 2014.

M. Derry and B. Argall. Extending Myoelectric Prosthesis Control with Shapable Automation: A First Assessment. In Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction (HRI), Bielefeld, Germany, March 2014.

A. Goil, M. Derry, and B. Argall. Using Machine Learning to Blend Human and Robot Controls for Assisted Wheelchair Navigation. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), Seattle, Washington, USA, 2013.

M. Derry and B. Argall. Automated Doorway Detection for Assistive Shared-Control Wheelchairs. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.

B. D. Argall. Machine Learning for Shared Control with Assistive Machines. In ICRA Workshop on Autonomous Learning: From Machine Learning to Learning in Real-world Autonomous Systems, Karlsruhe, Germany, May 2013.

T. D. Murphey and B. D. Argall. Making Robotic Marionettes Perform. In ICRA Workshop on Robotics and Performance Arts: Reciprocal Influences, Minneapolis, Minnesota, USA, May 2012.

December 2016

Brenna is named one of the 40 under 40 by Crain’s Chicago Business.

September 2016

Our lab’s work has been in the news! Check out the coverage in Digital TrendsCrain’s Chicago BusinessThe Big Ten Network and NPR’s Morning Edition.

Alex’s article Real-Time Natural Language Corrections for Assistive Manipulation Tasks is accepted to IJRR.

For an overview of what we are about, check out Brenna’s recent CMU Robotics Institute Seminar:

June 2016

Michael, Mahdieh and Ahmetcan’s paper An Analysis of Degraded Communication Channels in Human-Robot Teaming and Implications for Dynamic Autonomy Allocation is accepted to FSR.

Alex’s paper Trust-based Control for Safe and Stable Shared Control Between Humans and Robots is accepted to RA-L and CASE.

Deepak and Siddarth’s paper User-Driven Customization of Shared Autonomy with an Assistive Robotic Arm: A First Assessment is accepted to RA-L and CASE.

Mahdieh’s paper Automated Incline and Drop-off Detection for Assistive Powered Wheelchairs is accepted to RO-MAN.

April 2016

Manuela Veloso visits our lab. Check out the family photo!

Ahmetcan’s article The Effect Robotic Wheelchair Control Paradigm and Interface on User Performance, Effort and Preference: An Experimental Assessment is accepted to RAS.

Deepak’s paper Mode Switch Assistance To Maximize Human Intent Disambiguation is accepted to RSS.

Alex’s paper Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics is accepted to RSS.

Ahmetcan’s paper Prediction of User Preference over Shared-Control Paradigms for a Robotic Wheelchair is accepted to ICORR.

The lab demos in the Museum of Science and Industry for National Robotics Week.

March 2016

We moved! RIC is now the Shirely Ryan AbilityLab. 

February 2016

Brenna wins the NSF Early Faculty CAREER Award, for her proposal Robot Learning from Motor-Impaired Teachers and Task Partners.

Brenna wins an ONR award, Dynamic Allocation of Autonomy for Limited-Bandwidth Human-Robot Teams Based on Measures of Trust in the Human.

January 2016

Alex’s paper Path Planning under Kinematic Constraints for Shared Human-Robot Control is accepted to ICAPS.

Siddarth’s paper Grasp Detection for Assistive Robotic Manipulation is accepted to ICRA.

Brenna wins an NIH SBIR award, Semi-autonomous Robotic Powered Wheelchair Functionality (collaboration with Innovative Design Labs).

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