On Monday Mar. 27 2017, we welcome:
Aaron Ames (California Institute of Technology)
Bren Professor, Mechanical & Civil Engineering
Control & Dynamical Systems
Optimization-Based Control of Dynamic Robotic Systems
Humans have the ability to locomote with deceptive ease, navigating everything from daily environments to uneven and uncertain terrain with efficiency and robustness. With the goal of achieving these capabilities on robotic systems—ranging from legged robots, to robotic assistive devices to wheeled and aerial vehicles—this talk will present a unified formal framework for realizing dynamic behaviors in a provably correct and safety-critical fashion, along with the application of these ideas experimentally on a wide variety of robotic systems.
Beginning at the level of behavior synthesis, a unified control framework will be presented that balances achieving control objectives—represented by control Lyapunov functions (CLFs)—with safety constraints—encoded by control barrier functions (CBFs)—in the context of optimization-based controllers that can be solved efficiently online. The application of these ideas to humanoid robots will first be explored, wherein the means of achieving efficient dynamic locomotion will be presented together with corresponding experimental validation. The translation of these ideas to robotic assistive devices, and specifically powered prostheses, will be described in the context of custom-built hardware. Finally, the extension of these concepts to safety-critical systems—including automotive applications, multi-agent systems, and swarms of quadrotors—will be discussed. Therefore, this talk will explore a formal approach to achieving dynamic behaviors on robotic systems, together with the validation of these concepts experimentally on hardware platforms ranging from quadrotors, to powered prostheses to humanoid robots.