Advanced Robotics | Probabilistic Reasoning | Optimization Techniques

Explore the mathematical foundations and algorithms powering modern robotic systems. Dive into Markov Decision Processes, function approximation, and optimization techniques with broad AI applications.

Introduction

The course introduces the math and algorithms underneath state-of-the-art robotic systems. The majority of these techniques are heavily based on probabilistic reasoning and optimization---two areas with wide applicability in modern Artificial Intelligence. An intended side-effect of the course is to generally strengthen your expertise in these two areas.

Highlights

• Covers advanced topics in robotics, including Markov Decision Processes, function approximation, convex and non-convex optimization, and motion planning
• Focuses on the mathematical foundations and algorithms that power modern robotic systems
• Provides an in-depth exploration of probabilistic reasoning and optimization techniques with broad applications in AI

Recommendation

This course is recommended for students interested in robotics, artificial intelligence, and the mathematical foundations of advanced technologies. It provides a strong background in key areas of modern robotics and is well-suited for those looking to deepen their expertise in these fields.