Sheng-Wen Cheng
Sheng-Wen (Colin) Cheng is a system software engineer with the Platform Security Controller (PSC) team at NVIDIA, where he develops secure bootloader software to ensure system integrity during the boot process. Beyond his role at NVIDIA, he builds low-level software at the intersection of robotics, control engineering, and real-time systems.
He is also an active open-source contributor and has presented his work at leading open-source events, including Open Source Summit organized by the Linux Foundation.
Sessions
This talk introduces the basic ideas behind quadrotor optimal control and reinforcement learning from a practical, beginner-friendly perspective. We will discuss how position, velocity, attitude, and angular velocity are used to describe the drone state, and how a controller converts tracking errors into motor commands.
Several representative control approaches will be introduced, including the Linear Quadratic Regulator (LQR), H∞ robust control, Model Predictive Control (MPC), and Reinforcement Learning (RL). The talk will explain the intuition behind each method: what it tries to optimize, what kinds of problems it handles well, and what trade-offs appear in practice.
The examples will be based on RotorBench, an open-source Python-based quadrotor control benchmarking framework. More details about the project are available at: https://github.com/shengwen-tw/rotor-bench