Course Overview

Optimization algorithms form the bedrock of much of robotics, from machine learning to control, state estimation, and simulation. However, the research literature on these topics is vast and different communities often use different notation and terminology to describe similar ideas, making it difficult to see the deep connections between these areas.

The overall goal of the Optimization for Robotics Summer School is to provide roboticists with a deeper understanding of the connections between seemingly disparate topics and to motivate the cross-pollination of ideas across subfields. No specialized background in optimization is expected of attendees. All content will also be posted online and released as open-source after the summer school for the benefit of the robotics community.

We will cover: 1) A grounding in the fundamental mathematics and numerical algorithms of optimization; 2) A selection of robotics topics, including learning, control, state estimation, and simulation, from a unified optimization perspective; 3)Instructor-guided hands-on coding exercises to gain practical experience.

My Roles

• Co-desgined the summer school
• Co-designed and gave lectures
• Supported website developemnt