Publications

2024

[60] A. Thompson, F. Rizzoglio, F. A. Neylon, D. R. Barsoum, L. E. Ammon, M. N. McCune, L. Miller and B. Argall. An Evolution of Assistive Robot Arm Control to Meet End-User Ability. In Companion of the ACM/IEEE International Conference on Human-Robot Interaction, 2024.

2023

[59] M. Nejati-Javaremi, L. Y.C. Loke and B. Argall. Experimental Validation of Interface-Aware Assistance for 7-DoF Robot Arm Teleoperation. In Proceedings of the International Symposium on Experimental Robotics (ISER), 2023.

[58] J. M. Lee, T. Gebrekristos, D. De Santis, M. Nejati-Javaremi, D. Gopinath, B. Parikh, F. A. Mussa-Ivaldi and B. Argall. Learning to Control Complex Robots Using High-Dimensional Body-Machine Interfaces. To appear in ACM Transactions on Human-Robot Interaction, 2023.

[57] L. Y. C. Loke, D. Barsoum, T. Murphey and B. Argall. Characterizing Eye Gaze for Assistive Device Control. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), 2023.

[56] J. M. Lee, T. Gebrekristos, D. De Santis, M. Nejati-Javaremi, D. Gopinath1, B. Parikh, F. A. Mussa-Ivaldi, and B. D. Argall. An Exploratory Multi-Session Study of Learning High-Dimensional Body-Machine Interfacing for Assistive Robot Control. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), 2023.

[55] A. Thompson*, M. Lee*, L. Y.C. Loke*, B. Martinez*, K. Rowland*, M. Nejati Javaremi* and B. Argall. Identifying Accessibility Barriers to Robotics Research. In RSS 2023 Workshop on Lowering Barriers for Robotics Research, Daegu, Korea, 2023.

2022

[54] M. Nejati Javaremi, S. Sinaga, Y. Jin, M. Elwin and B. Argall. The Interface Usage Skills Test: An Open Source Tool for Real-Time Quantitative Evaluation for Clinicians and Researchers. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), 2022.

[53] A. Thompson*, Y. C. Loke* and B. Argall. Control Interface Remapping for Bias-Aware Assistive Teleoperation. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), 2022.

[52] D. E. Gopinath, A. Thompson  and B. Argall. Information Theoretic Intent Disambiguation via Contextual Nudges for Assistive Shared Control. In Proceedings of the Workshop on the Algorithmic Foundations of Robotics (WAFR), 2022.

[51] D. E. Gopinath. Active Intent Disambiguation, Control Interpretation, and Arbitration for Assistive Robotics. PhD Dissertation, Northwestern University, 2022.

2021

[50] J. M. Lee, T. Gebrekristos, D. De Santis, M. Nejati-Javaremi, D. Gopinath, B. Parikh, F. A. Mussa-Ivaldi and B. D. Argall. Learning to Control Complex Robots Using High-Dimensional Interfaces: Preliminary Insights. In Proceedings of the AAAI Fall Symposium on AI for Human-Robot Interaction, 2021.

[49] M. Nejati, Di Wu and B. Argall. The Impact of Control Interface on Features of Heart Rate Variability. In Proceedings of the IEEE Engineering in Medicine and Biology Society Conference (EMBC), 2021.

[48] C. Miller, T. Gebrekristos, M. Young and B. Argall. An Analysis of Human-Robot Information Streams to Inform Dynamic Autonomy Allocation. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.

[47] H. Kress-Gazit, K. Eder, G. Hoffman, H. Admoni, B. Argall, R. Ehlers, C. Heckman, N. Jansen, R. Knepper, J. Křetínský, S. Levy-Tzedek, J. Li, T. Murphey, L. Riek and D. Sadigh. Formalizing and Guaranteeing* Human-Robot Interaction. Communications of the ACM, 64(9), 78-84, 2021.

[46] D. Gopinath*, M. Nejati* and B. Argall. Customized Handling of Unintended Interface Operation in Assistive Robots. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), virtual, June 2021.

2020

[45] F. Lau*, D. Gopinath* and B. Argall. A JavaScript Framework for Crowdsourced Human-Robot Interaction Experiments: RemoteHRI. In Proceedings of the AAAI Fall Symposium on Trust and Explainability in Artificial Intelligence of Human-Robot Interaction, 2020.

[44] A. Broad, I. Abraham, T. Murphey and B. Argall. Model-based Shared Control of Data-Driven Human-Machine Systems. International Journal of Robotics Research, 2020.

[43] I. Abraham, A. Broad, A. Pinosky, B. Argall and T. Murphey. Hybrid Control of Motor Learning Skills. In Proceedings of the Workshop on the Algorithmic Foundations of Robotics (WAFR), June 2020.

[42] D. Gopinath and B. Argall. Active Intent Disambiguation for Shared-Control Robots. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(6), 1497-1506, 2020.

2019

[41] A. Broad. Generalizable Data-driven Models for Personalized Shared Control of Human-Machine Systems through Machine Learning. PhD Dissertation, Northwestern University, 2019.

[40] S. Jain. Mathematical Models for Human-Robot Systems in Assistive Robotics: Perception, Inference, and Assistance. PhD Dissertation, Northwestern University, 2019.

[39] S. Jain and B. Argall. Probabilistic Human Intent Recognition for Shared Autonomy in Assistive Robotics. Transactions on Human-Robot Interaction, 9(1), 2019.

[38] M. Nejati Javaremi, M. Young and B. Argall. Wheelchair Interface Usage Assessment Tasks and Performance Measures for Assistive Robots. In ACRM Annual Conference: Progress in Rehabilitation Research, Chicago, Ilinois, USA, Nov. 2019. (Conference with abstract-only proceedings.)

[37] M. Young, M. Nejati and B. Argall. Discrete N-Dimensional Entropy of Behavior: DNDEB. In Proceedings of the IEEE International Conference on Intelligent Robots (IROS), Macao, China, October 2019.

[36] 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.

[35] 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, June 2019.

[34] M. Nejati Javaremi, M. Young and B. Argall. Interface Modality Informing Assistive Autonomy. In ICRA 2019 Workshop on Human Movement Science for Physical Human-Robot Collaboration, Montreal, Canada, May 2019.

[33] 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.

2018

[32] 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.

[31] 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, October 2018.

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

2017

[29] 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.

[28] 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.

[27] 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.

[26] 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.

[25] 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.

[24] 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.

[23] 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.

[22] 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

[21] 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.)

[20] 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.)

2016

[19] 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.

[18] 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.

[17] 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.

[16] 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.

[15] 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.

2015

[14] 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.

[13] 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.

[12] 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.

[11]  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)

2014

[10] 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.

[9] 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.

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

[7]  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.

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

[5] 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.

2013

[4] 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.

[3] 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.

[2] 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.

2012

[1]  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.