Physical Intelligence
Spring 2026. ESE 6510. Tue / Thu 10:15-11:45. Berger Auditorium (basement floor of Skirkanich Hall)
Announcements
First day of class.
Classes will start on Jan 15th. On this webpage, you can find all learning-related materials. Looking forward to the second edition of the class!
Course Overview
Why don’t we yet have a foundation model that can operate robots in the physical world? What makes applying the standard pre-training approach so uniquely challenging in robotics? And what recent advances are pushing the boundaries of what’s possible in real-world applications?
This course offers a structured framework to explore these questions. We will study the mathematical foundations of techniques for learning-based decision-making and examine how these methods are deployed in robotic systems. Through a combination of lectures, hands-on projects (including a drone race!), and guest presentations from leading experts in the field, students will gain a deep understanding of the state-of-the-art decision-making systems and their challenges when applied to robotics.
Prerequisites
This is a graduate-level course. Students are expected to have prior knowledge in deep learning and robotics, such as the topics covered in Robot Learning (ESE 650), Applied Machine Learning (CIS 5190), and Introduction to Robotics (MEAM-520).
Previous Offerings
This class was also offered in Fall 2025.
Schedule
Foundation
- JAN 15
- JAN 20
- What is a Robot? Actuation
- JAN 22
- What is a Robot? Perception
- JAN 29
- Quiz on What is a Robot + Intro to Probability
- Notes (pp 1-2)
Reinforcement Learning
Sim2Real
Imitation Learning
Frontiers
- APR 14
- Guest Lecture
- Abhishek Gupta
- APR 16
- Guest Lecture
- Kuan Fang
- APR 21
- Guest Lecture
- Boyuan Chen
- APR 23
- Challenges Ahead
- Slides
- APR 28
- Race Day (Phase II)
Instructor
Teaching Assistants
Related Courses
Robots that learn, UC Berkeley.
Robotics Manipulation, MIT.
Deep Reinforcement Learning: CMU version UC Berkeley version.
Introduction to Robot Learning, CMU.
Embodied AI Safety, CMU. This course is not only very interesting, but also has an awesome webpage.