Prof. Humbert’s research include perception, reduction and feedback principles in biology. Nervous systems have evolved to make useful reductions of sensory-rich high dimensional data, forming simple representations that allow animals to perform well with limited computation in the presence of uncertainty. His laboratory works with biologists to apply control- and information-theoretic tools to formalize these principles in small animals such as insects, providing insight into the biology and resulting in novel, robust and computationally efficient solutions for small-scale engineered systems.
Bio-inspired sensing, estimation, and control, insect visual processing, autonomous robotics, flight dynamics, flight control and avionics, dynamical systems, modeling of biological systems, soft robotics
ASEN 5014 - Linear Control Systems
Introduces the theory of linear systems, including vector spaces, linear equations, structure of linear operators, state space descriptions of dynamic systems, and state feedback control methods. Recommended prerequisite: ASEN 3200 or equivalent or instructor consent required.
MCEN 2043 - Dynamics
Spring 2018 / Spring 2019
Covers dynamic behavior of particle systems and rigid bodies; 2-D and 3-D kinematics and kinetics; impulse, momentum, potential, and kinetic energy; and work, collision, and vibration.