Education is not the filling of a pail, but the lighting of a fire.Plutarch
Courses at Technical University of Munich
Interested in machine learning and control for robotics? Join our summer-term courses offered at TUM for the first time. Prerequisites are a strong maths and control theory background. The courses are now open for registration!
Control for Robotics: from Optimal Control to Reinforcement Learning
| Terms Offered: | Every Summer Semester Since 2023 |
| Target Audience: | Wahlmodul (Elective Module) for Master Students |
| Instructor: | Prof. Angela Schoellig |
| Topics Covered: | This is an advanced control course with machine learning elements. In particular, this course presents optimal control, learning-based control, and reinforcement learning principles from the perspective of robotics applications. The course covers the foundations of optimal control and derives practical control algorithms that leverage first-principle robot models and data collected from the robot system. Real-world challenges such as disturbances, state estimation errors, and model errors are addressed, and adaptive and reinforcement learning approaches are derived to address these challenges. |
Semantics in Robot Perception and Decision-Making Seminar Course
| Terms Offered: | Every Semester Since Winter 2024 |
| Target Audience: | Wissenschaftliches Seminar (Scientific Seminar) for Graduate Students |
| Instructors: | Prof. Angela Schoellig, Prof. Angela Dai, Ilyass Taouil, and Dr. SiQi Zhou |
| Topics Covered: | Students will gain knowledge in robot decision-making by critically reviewing existing literature in this field, with a focus on semantics-informed approaches. The specific topics covered will change each term. Example topics include safe robot learning, learning from demonstration, language-conditioned robot learning, spatial AI, and 3D scene understanding. |
Machine Learning and Robotics Seminar Course
| Terms Offered: | Every Semester Since Summer 2023 |
| Target Audience: | Wissenschaftliches Seminar (Scientific Seminar) for Graduate Students |
| Instructor: | Prof. Angela Schoellig |
| Topics Covered: | Students will learn about robot learning and control by critically reviewing existing literature in this field. Topics will vary each term. Example topics include machine learning models for robotics, human-centred robot learning, learning of interactive tasks, learning from demonstration, safe robot learning, and multi-robot learning. |
Autonomous Drone Racing Project Course
| Terms Offered: | Every Semester Since Summer 2023 |
| Target Audience: | Projektpraktikum (Project Internship) for Graduate Students |
| Instructor: | Prof. Angela Schoellig |
| Topics Covered: | This course was formerly called the “Robot Learning and Control Project Course.” Students will gain hands-on experience in robot learning and control by developing their own comprehensive hardware/software solution for a drone racing problem. Student teams work jointly on the hardware and software solution, and develop a robot demonstration to showcase their results. The main goal of this course is to teach robotics problem solving skills as well as project management and teamwork. Having experience in Python or C++ programming would be a plus. |
| Former Name: | Robot Learning and Control Project Course |
Courses at University of Toronto
Undergraduate
ROB310: Mathematics for Robotics
| Terms Offered: | Fall 2015-20 |
| Target Audience: | Third-year undergraduate course, Engineering Science |
| Instructor: | Prof. Angela Schoellig |
| Topics Covered: | Advanced mathematical concepts that are particularly relevant for robotics (including concepts from optimization, probability theory, linear algebra and numerical methods). >> Syllabus >> Reading List |
AER372: Control Systems
| Terms Offered: | Spring 2014-16 |
| Target Audience: | Third-year undergraduate course, Engineering Science |
| Instructors: | Prof. Angela Schoellig |
| Topics Covered: | Introduction to feedback control (including modelling of physical systems, analysis of dynamic behavior, concept of stability and performance, design of feedback controllers for single-input single-output systems). >> Syllabus |
Graduate
AER1216: Fundamentals of UAVs
| Terms Offered: | Spring 2016; Fall 2016-18, 2020 |
| Target Audience: | Graduate course |
| Instructors: | Prof. Hugh Liu (course coordinator), Prof. Angela Schoellig (co-lecturer), and others |
| Topics Covered: | UAV design process: configurations (fixed-wing, multi-rotor), aerodynamics, performance (range, endurance, climb rate, etc), propulsion (propellers, motors, etc), stability/control, structures. >> Syllabus |
AER1217: Development of Autonomous UAVs
| Terms Offered: | Spring 2017, 2018, 2021 |
| Target Audience: | Graduate course |
| Instructors: | Prof. Hugh Liu (course coordinator), Prof. Angela Schoellig (co-lecturer), and others |
| Topics Covered: | Quadrotor dynamics and control, navigation for UAVs, path planning for UAVs, computer vision for UAVs, instrumentation and sensor payloads for UAVs. >> Syllabus |
AER1517: Control for Robotics
| Terms Offered: | Spring 2019, 2020 |
| Target Audience: | Graduate course |
| Instructors: | Prof. Angela Schoellig |
| Topics Covered: | Introduction to optimal, adaptive and learning control principles from the perspective of robotics applications (including discrete-time and continuous-time optimal control, model predictive control, reinforcement learning and other recent learning-based control techniques). >> Syllabus |
Courses at ETH Zurich
151-0563-01: Dynamic Programming and Optimal Control
| Terms Offered: | Fall 2008, 2009, 2012 |
| Target Audience: | Graduate course |
| Instructors: | Prof. Raffaello D’Andrea (Lecturer 2008, 2009), Angela Schoellig (Lecturer 2012; Teaching Assistant 2008, 2009) |
| Topics Covered: | Dynamic programming algorithm, deterministic systems and shortest path problems, infinite horizon problems, value/policy iteration, deterministic continuous-time optimal control. >> Syllabus >> Course Website 2008 >> Course Website 2009 >> Course Website 2012 |
151-0566-00: Recursive Estimation
| Terms Offered: | Spring 2010, 2011 |
| Target Audience: | Graduate course |
| Instructors: | Prof. Raffaello D’Andrea (Lecturer), Angela Schoellig (Teaching Assistant) |
| Topics Covered: | Introduction to estimation; probability review; Bayes theorem; Bayesian tracking; standard Kalman filter; extended Kalman filter; particle filtering; observers and the separation principle. >> Course Website 2010 >> Course Website 2011 |
Online Courses
Udacity Flying Car Nanodegree
| Terms Offered: | Available since February 2018 |
| Target Audience: | Online degree |
| Instructors: | Prof. Nicholas Roy, Prof. Angela Schoellig, Prof. Sebastian Thrun, Prof. Raffaello D’Andrea |
| Topics Covered: | 3D motion planning, controls, and estimation for multi-rotor and fixed-wing aircrafts. >> Syllabus >> Course Website |
