Skip to main content

Todd MurpheyProfessor of Mechanical Engineering

Professor Murphey's research focuses on computational methods in dynamics and control, with applications in neuroscience, health science, robotics, and automation. The group focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control.  The mathematical approaches used by the group lead to many orders of magnitude improvement in computational efficiency for reliable real-time implementation. Applications include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation. 

Curriculum vitae

Interactive & Emergent Autonomy Lab

In the Interactive and Emergent Autonomy Lab, our research focuses on computational methods in data-driven control, information theory in physical systems, and embodied intelligence. We investigate how both autonomous systems and biological systems interact with their environments (and, in some cases, with each other) to learn and improve their behaviors. This work often involves mathematical modeling, development of new mathematical tools, algorithmic implementation and programming, and experimentation.

Example projects include robotic exploration using electrosenserobotic exploration using mechanical contact, human-in-the-loop control, and shared control for rehabilitation/assistive devices. We also work in the field of algorithmic matter, where we develop computational models to enable the design of microrobots with minimal actuation, sensing, and computation.

Learn more about our projects.

Interactive & Emergent Autonomy Lab GitHub

California Institute of Technology Pasadena, CA
Ph.D. in Control and Dynamical Systems, 2002
Thesis: Control of Multiple Model Systems

University of Arizona Tucson, AZ
B.S. in Mathematics, summa cum laude, 1997

Professor Murphey has developed the ME 314 Machine Dynamics course, focusing on the application of variational analysis to simulation anddesign of mechanisms.  He has additionally developed ME 454, anintroduction to numerical methods in optimal control.  In 2013 he taught an online version of one of the Engineering Analysis courses as a Coursera Massive Open Online Course (MOOC) (more information can be found at Coursera class Everything is the Same: Modeling Engineered Systems).  In all these courses, Professor Murphey focuses on project-based learning.  He has been a featured speaker at the National Academy of Engineering Frontiers of Engineering Education Workshop (see his blog here).

Science Robotics

Katie's paper Ergodicity reveals assistance and learning from physical human-robot interaction was published in Science Robotics in April 2019. In the paper, information theoretic principles were applied to the investigation of physical human-robot interaction.

NSF Science Nation

Engineering highly adaptable robots requires new tools for new rules. NSF-funded research aiming to make it easier for humans to work directly with a robotic partner in applications such as physical therapy.

Control Systems Society

Ahalya won third place in the 2017 IEEE Control Systems Society Video Clip Contest with her video Autonomous Robot Drawing: From Distribution to Actions using Feedback.

CBS Chicago

Professor Murphey was interviewed as part of a CBS story on robots improving productivity.

Berrueta, T., I. Abraham, and T. D. Murphey, "Experimental Applications of the Koopman Operator in Active Learning for Control", The Koopman Operator in Systems and Control: Theory, Numerics, and Applications: Springer, In Press. 

Schultz, J. A., E. Johnson, and T. D. Murphey, "Trajectory Optimization in Discrete Mechanics", Differential-Geometric Methods in Computational Multibody System Dynamics: Springer International Publishing, In Press. Google Scholar 

Pervan, A., and T. D. Murphey, "Algorithmic materials: Embedding computation within material properties for autonomy", Robotic Systems and Autonomous Platforms: Woodhead Publishing, pp. 197-221, 2019. Google Scholar 

Kalinowska, A., T. Berrueta, and T. D. Murphey, "Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device", International Conference on Robotics and Automation (ICRA), 2019. Google Scholar 

Berrueta, T., A. Pervan, K. Fitzsimons, and T. D. Murphey, "Dynamical System Segmentation for Information Measures in Motion", IEEE Robotics and Automation Letters, vol. 4, issue 1, pp. 169 - 176, 01/2019. Google Scholar 

Fitzsimons, K., A. Maria Acosta, J. Dewald, and T. D. Murphey, "Ergodicity reveals assistance and learning from physical human-robot interaction", Science: Robotics, vol. 4, issue 29, 2019. Google Scholar 

Abraham, I., A. Prabhakar, and T. D. Murphey, "Active Area Coverage from Equilibrium", Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018. Google Scholar 

Abraham, I., A. Mavrommati, and T. D. Murphey, "Data-Driven Measurement Models for Active Localization in Sparse Environments",Proceedings of Robotics: Science and Systems, 2018. Google Scholar 

Abraham, I., and T. D. Murphey, "Decentralized Ergodic Control: Distribution-Driven Sensing and Exploration for Multiagent Systems", IEEE Robotics and Automation Letters, vol. 3, pp. 2987-2994, Oct, 2018. Google Scholar 

Fan, T., J. A. Schultz, and T. D. Murphey, "Efficient Computation of Higher-Order Variational Integrators in Robotic Simulation and Trajectory Optimization", Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018. Google Scholar 

Mamakoukas, G., M. A. MacIver, and T. D. Murphey, "Feedback Synthesis For Underactuated Systems Using Sequential Second-Order Needle Variations", The International Journal of Robotics Research, 2018. Google Scholar 

Tzorakoleftherakis, E., and T. D. Murphey, "Iterative Sequential Action Control for Stable, Model-Based Control of Nonlinear Systems", IEEE Transactions on Automatic Control, 2018. Google Scholar 

Pervan, A., and T. D. Murphey, "Low Complexity Control Policy Synthesis for Embodied Computation in Synthetic Cells", Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018. Google Scholar 

Kalinowska, A., K. Fitzsimons, J. Dewald, and T. D. Murphey, "Online User Assessment for Minimal Intervention During Task-Based Robotic Assistance", Robotics: Science & Systems, 06/2018. Google Scholar

Broad, A., T. D. Murphey, and B. Argall, "Operation and Imitation under Safety-Aware Shared Control", Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018. Google Scholar 

Mavrommati, A., E. Tzorakoleftherakis, I. Abraham, and T. D. Murphey, "Real-Time Area Coverage and Target Localization Using Receding-Horizon Ergodic Exploration", IEEE Transactions on Robotics, issue 34, pp. 62-80, Jan-01-2017, 2018. Google Scholar

Broad, A., I. Abraham, T. D. Murphey, and B. Argall, "Structured Neural Network Dynamics for Model-based Control", Learning and Inference in Robotics (LAIR) Workshop, 2018. Google Scholar 

Mamakoukas, G., M. A. MacIver, and T. D. Murphey, "Superlinear Convergence Using Controls Based on Second-Order Needle Variations", Conference on Decision and Control, 2018. Google Scholar 

Wilson, A. D., J. A. Schultz, A. Ansari, and T. D. Murphey, "Dynamic Task Execution Using Active Parameter Identification With the Baxter Research Robot", IEEE Transactions on Automation Science and Engineering, vol. 14, issue 1, pp. 391-397, 2017. Google Scholar 

Abraham, I., A. Prabhakar, M. J. Z. Hartmann, and T. D. Murphey, "Ergodic Exploration using Binary Sensing for Non-Parametric Shape Estimation", IEEE Robotics and Automation Letters, vol. 2, issue 2, pp. 827-834, 2017. Google Scholar 

Mamakoukas, G., M. A. MacIver, and T. D. Murphey, "Feedback Synthesis for Controllable Underactuated Systems using Sequential Second Order Actions", Robotics: Science and Systems, 2017. Google Scholar 

Flaßkamp, K., A. Ansari, and T. D. Murphey, "Hybrid Control for Tracking of Invariant Manifolds", Nonlinear Analysis: Hybrid Systems, 2017. Google Scholar 

MacIver, M. A., L. Schmitz, U. Mugan, T. D. Murphey, and C. Mobley, "Massive increase in visual range preceded the origin of terrestrial vertebrates", Proceeding of the National Academy of Sciences, vol. 114, pp. E2375-E2384, 03/2017. Google Scholar 

Abraham, I., G. De La Torre, and T. D. Murphey, "Model-Based Control Using Koopman Operators", Robotics: Science and Systems, 2017. Google Scholar 

Tzorakoleftherakis, E., T. D. Murphey, and R. A. Scheidt, "Augmenting sensorimotor control using “goal‑aware” vibrotactile stimulation during reaching and manipulation behaviors", Experimental Brain Research, 04/2016. 

Prabhakar, A., A. Mavrommati, J. A. Schultz, and T. D. Murphey, "Autonomous Visual Rendering using Physical Motion", Workshop on the Algorithmic Foundations in Robotics (WAFR) 2016, 2016. Google Scholar 

Miller, L. M., Y. Silverman, M. A. MacIver, and T. D. Murphey, "Ergodic Exploration of Distributed Information", Transactions on Robotics, vol. 32, issue 1, pp. 36-52, 2016. Google Scholar 

Tzorakoleftherakis, E., A. Ansari, A. D. Wilson, J. A. Schultz, and T. D. Murphey, "Model-Based Reactive Control for Hybrid and High-Dimensional Robotic Systems", IEEE Robotics and Automation Letters, vol. 1, issue 1, pp. 431-438, 2016. Google Scholar 

Fitzsimons, K., E. Tzorakoleftherakis, and T. D. Murphey, "Optimal Human-In-The-Loop Interfaces Based on Maxwell's Demon", American Control Conference (ACC), Boston, MA, pp. 4397-4402, 07/2016. Google Scholar 

Ansari, A., and T. D. Murphey, "Sequential Action Control: Closed-Form Optimal Control for Nonlinear Systems", IEEE Transactions on Robotics, vol. 32, issue 5, pp. 1196 - 1214, Oct. 2016. Google Scholar

Back to top