5 papers
Learning for Layered Safety-Critical Control with Predictive Control Barrier Functions
William D. Compton, Max H. Cohen, Aaron D. Ames
Safety filters leveraging control barrier functions (CBFs) are highly effective for enforcing safe behavior on complex systems. It is often easier to synthesize CBFs for a Reduced…
Safety-Critical Controller Synthesis with Reduced-Order Models
Max H. Cohen, Noel Csomay-Shanklin, William D. Compton +2
Reduced-order models (ROMs) provide lower dimensional representations of complex systems, capturing their salient features while simplifying control design. Building on previous wo…
Dynamic Tube MPC: Learning Tube Dynamics with Massively Parallel Simulation for Robust Safety in Practice
William D. Compton, Noel Csomay-Shanklin, Cole Johnson +1
Safe navigation of cluttered environments is a critical challenge in robotics. It is typically approached by separating the planning and tracking problems, with planning executed o…
Dynamically Feasible Path Planning in Cluttered Environments via Reachable Bezier Polytopes
Noel Csomay-Shanklin, William D. Compton, Aaron D. Ames
The deployment of robotic systems in real world environments requires the ability to quickly produce paths through cluttered, non-convex spaces. These planned trajectories must be…
Constructive Nonlinear Control of Underactuated Systems via Zero Dynamics Policies
William Compton, Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin +2
Stabilizing underactuated systems is an inherently challenging control task due to fundamental limitations on how the control input affects the unactuated dynamics. Decomposing the…