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Todd David Murphey

  • 1056 Citations
2000 …2026
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Personal profile

Education/Academic qualification

Control and Dynamical Systems, PhD, California Institute of Technology

… → 2002

Mathematics (summa cum laude), BS, University of Arizona

Research interests

  • Modeling and control of complex mechanisms
  • Puppets
  • Robotics

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Trajectories Engineering & Materials Science
Robotics Engineering & Materials Science
Mechanics Engineering & Materials Science
Kinematics Engineering & Materials Science
Robots Engineering & Materials Science
Controllers Engineering & Materials Science
Feedback Engineering & Materials Science
Nonlinear systems Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Grants 2008 2026

Formal Foundations of Algorithmic Matter and Emergent Computation

Murphey, T. D.

Georgia Institute of Technology, Army Research Office

7/1/19 → 6/30/26

Project: Research project

Learning systems
Communication
Uncertainty

Interaction and Perception: Multi-Source Spectral Framework for Human-Swarm Collaboration

Murphey, T. D. & Colgate, E.

Space and Naval Warfare Systems Center Pacific

5/20/19 → 2/19/20

Project: Research project

Interfaces (computer)
Haptic interfaces
Touch screens
Virtual reality

CPS: Medium: Information based Control of Cyber-Physical Systems operating in uncertain environments

Argall, B. D. & Murphey, T. D.

National Science Foundation

9/15/18 → 8/31/21

Project: Research project

Physics
Cyber Physical System
Uncertainty

RI: Small: Collaborative Research: Information-driven Autonomous Exploration in Uncertain Underwater Environments

Murphey, T. D.

National Science Foundation

9/1/17 → 8/31/20

Project: Research project

Robotics
Robots
Fish
Museums
Real time control

Stability and Optimality Properties of Sequential Action Control for Nonlinear and Hybrid Systems

Murphey, T. D.

National Science Foundation

8/1/17 → 7/31/20

Project: Research project

Hybrid systems
Nonlinear systems
Lie groups
Museums
Students

Research Output 2000 2019

Active Learning of Dynamics for Data-Driven Control Using Koopman Operators

Abraham, I. & Murphey, T. D., Oct 2019, In : IEEE Transactions on Robotics. 35, 5, p. 1071-1083 13 p., 8759089.

Research output: Contribution to journal › Article

Controllers
Robotics
Problem-Based Learning
Mathematical operators
Nonlinear systems

Adaptive single action control policies for linearly parameterized systems ∗

Ennasr, O., Mamakoukas, G., Castaño, M., Coleman, D., Murphey, T. & Tan, X., Jan 1 2019, Advanced Driver Assistance and Autonomous Technologies; Advances in Control Design Methods; Advances in Robotics; Automotive Systems; Design, Modeling, Analysis, and Control of Assistive and Rehabilitation Devices; Diagnostics and Detection; Dynamics and Control of Human-Robot Systems; Energy Optimization for Intelligent Vehicle Systems; Estimation and Identification; Manufacturing. American Society of Mechanical Engineers (ASME), V001T02A004. (ASME 2019 Dynamic Systems and Control Conference, DSCC 2019; vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Gliders
Controllers
Needles
Parameter estimation
Fish

Data-driven gait segmentation for walking assistance in a lower-limb assistive device

Kalinowska, A., Berrueta, T. A., Zoss, A. & Murphey, T., May 2019, 2019 International Conference on Robotics and Automation, ICRA 2019. Institute of Electrical and Electronics Engineers Inc., p. 1390-1396 7 p. 8794416. (Proceedings - IEEE International Conference on Robotics and Automation; vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Contact sensors
Hoppers
Model predictive control
Hybrid systems
Patient rehabilitation

Dynamical system segmentation for information measures in motion

Berrueta, T. A., Pervan, A., Fitzsimons, K. & Murphey, T. D., Jan 1 2019, In : IEEE Robotics and Automation Letters. 4, 1, p. 169-176 8 p., 8552420.

Research output: Contribution to journal › Article

Information Measure
Dynamical systems
Segmentation
Dynamical system
Embodiment

Ergodicity reveals assistance and learning from physical human-robot interaction

Fitzsimons, K., Acosta, A. M., Dewald, J. P. A. & Murphey, T. D., Apr 10 2019, In : Science Robotics. 4, 29, eaav6079.

Research output: Contribution to journal › Article

Human-robot Interaction
Human robot interaction
Ergodicity
Robotics
Demonstrations