RESEARCH SUMMARY

The focus of our research is intelligent control in biology and engineering. The real-time control of a complex musculo-skeletal system such as the human body requires the generation of thousands of control signals per second. Humans' ability to accomplish difficult tasks - in the face of noise, delays, uncertainty, and constantly changing circumstances - suggests that these control signals are chosen rather intelligently and to a large extent online. We are trying to build a computational theory of the sensorimotor loops responsible for this moment-to-moment control and test the theory experimentally. We are also developing biologically-inspired algorithms for optimal control of complex dynamics. The specific projects in the lab fall in several categories: developing efficient control algorithms suitable for biomechanical systems; constructing control-theoretic models of behavioral phenomena; testing model predictions in motor psychophysics experiments; implementing systems-level models in recurrent neural networks; building compliant robots which we hope to be able to control using our new algorithms.

ACTIVE GRANTS

Optimal feedback control of goal-directed arm movements (NIH)
Toolbox for measurement, simulation and control of multi-joint movements (NIH)
Optimal control problems with linear Bellman equations (NSF)
Hierarchical approximations to optimal control (NSF)
Bayesian framework for sensorimotor control and learning (NIH)
Reverse-engineering the brain's ability to control the hand (NSF)

SELECTED PUBLICATIONS BY TOPIC   (full list here)

REVIEWS

Mathematical introduction to optimal control theory (2006)
Optimality principles in sensorimotor control (2004)

ENGINEERING CONTROL

Efficient computation of optimal actions (2009)
Eigenfunction approximations for linearly-solvable optimal control problems (2008)
Classic maximum principles and estimation-control dualities for nonliear stochastic systems (2008)
Hierarchical feedback control of redundant manipulators (2005)
Iterative LQG methods for constrained nonlinear stochastic systems (2005)
Optimal control and estimation with state- and control-dependent noise (2005)

BIOLOGICAL CONTROL

Parallels between sensory and motor information processing (2008)
Optimality of mixed muscle-movement representations (2008)
Evidence for the flexible strategies predicted by optimal feedback control (2007)
Unsupervised learning of sensorimotor primitives (2003)
Optimal feedback control as a theory of motor coordination (2002)
Direct cortical control of muscle activation (2000)

RELEVANT CONFERENCES

Advances in Computational Motor Control (ACMC)
American Control Conference (ACC)
IEEE Conference on Decision and Control (CDC)
Computational and Systems Neuroscience (CoSyNe)
Engineering in Medicine and Biology (EMBC)
Neural Control of Movement (NCM)
Neural Information Processing Systems (NIPS)
Society for Neuroscience Meeting (SFN)