1 citations · 1 across the 3 of their papers we have counts for
4 papers
Quadrotor Trajectory Tracking with Learned Dynamics: Joint Koopman-based Learning of System Models and Function Dictionaries
Carl Folkestad, Skylar X. Wei, Joel W. Burdick
Nonlinear dynamical effects are crucial to the operation of many agile robotic systems. Koopman-based model learning methods can capture these nonlinear dynamical system effects in…
Koopman NMPC: Koopman-based Learning and Nonlinear Model Predictive Control of Control-affine Systems
Carl Folkestad, Joel W. Burdick
Koopman-based learning methods can potentially be practical and powerful tools for dynamical robotic systems. However, common methods to construct Koopman representations seek to l…
Episodic Koopman Learning of Nonlinear Robot Dynamics with Application to Fast Multirotor Landing
Carl Folkestad, Daniel Pastor, Joel W. Burdick
This paper presents a novel episodic method to learn a robot's nonlinear dynamics model and an increasingly optimal control sequence for a set of tasks. The method is based on the…
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control
Carl Folkestad, Daniel Pastor, Igor Mezic +3
This paper presents a novel learning framework to construct Koopman eigenfunctions for unknown, nonlinear dynamics using data gathered from experiments. The learning framework can…