EE 546 B (Joint with ME 599 K and AA 546)
Sawyer B. Fuller, email@example.com
Despite decades of advancements in robotics, the capabilities of biological systems remain an elusive performance target. Watch a honeybee land on a flower buffeted by wind using a brain the size of a sesame seed, or a mountain goat navigate a sheer cliff. The dynamic motions and robustness to uncertainty exhibited by these and other animals far exceeds what has been so far achieved by their robotic counterparts.
In this course, students will learn about the latest findings about feedback control in animal motion. These have lead to an emerging, but by no means complete, understanding about how the transformations from sensory input to motor output can produce these capabilities. We will see how these findings, when applied to robots, have led to new insights. In addition to preparing students to pose questions at the cutting edge of robotics, this course will cover analytical concepts, methods, and tools that can be used to answer them.
Topics of particular emphasis will include
- reflexive control architectures
- using “mechanical intelligence” to reduce the burden of feedback control
- biomechanics of animal motion
- tools for modeling biological and robotic systems
including system dynamics and control theory (EE 447 or equivalent).
Topics will be developed through problem sets, demonstrations, assigned readings and presentations
of current literature, and analytical, numerical, or experimental projects.