Skip to main content

Scalable Algorithms for Physical Systems

We are seeking to develop more reliable algorithms for use with physical systems of varying dimensionality. Using these algorithms, we address issues of computational complexity and resource management in the design of algorithms for information determination, control, and sensitivity analysis which remain applicable to complicated nonlinear and impulsive systems. Our projects involve distributed control theory, hybrid control, sensitivity minimization, impacting systems, and information determination in continuous systems.


Core Researchers

Todd Murphey
Malcom MacIver
Jarvis Schultz
Alex Ansari
Vlad Seghete
Lauren Miller
Tim Caldwell
Andrew Wilson
Ahalya Prabhakar


Lanny Smoot at Disney Research 
Magnus Egerstedt at Georgia Tech

Related Publications

G. Mamakoukas, 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 PDF Video

A. Ansari, and T. D. Murphey, Sequential Action Control Closed-Form Optimal Control for Nonlinear Systems, IEEE Transactions on Robotics, vol. 32, no. 5, pp. 1196 - 1214, Oct. 2016/ 2016 Google Scholar PDF

G. Mamakoukas, M. A. MacIver, and T. D. Murphey, Sequential Action Control for Models of Underactuated Underwater Vehicles in a Planar Ideal Fluid, American Control Conference (ACC), Boston, MA, pp. 4500-4506, 07/2016/ 2016 Google Scholar PDF

A. Ansari, and T. D. Murphey, Control-On-Request Short-Burst Assistive Control for Long Time Horizon Improvement, American Control Conference (ACC), 2015 Google Scholar PDF

E. Jochum, J. A. Schultz, E. Johnson, and T. D. Murphey, Robotic Puppets and the Engineering of Autonomous Theater, Controls and Art, Springer International Publishing, pp. 107-128, 2014 Google Scholar

Back to top