Koopman operator theory provides a linear model of a dynamical system in the infinite dimensional space. In this post, I have summarized some basics of the Koopman operator and its extention to control systems.

Trajectory optimization has been widely used in robotics for various tasks such as navigation and manipulation. In this post, I have summarized related mathematical background and common computational approaches in trajectory optimization.

Reinforcement Learning (RL) has been a hot research area in the past two decades. It refers to the learning paradigm that an intelligent agent learns the optimal policy to take actions by interacting with the environments. In this post, I have summarized some basics of RL and provides an overview of classical approaches to RL.