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: | Summer 2023 |
| Target Audience: | Wahlmodul (Elective Module) for Master Students |
| Instructors: | 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. |
Machine Learning and Robotics Seminar Course
| Terms Offered: | Summer 2023 |
| Target Audience: | Wissenschaftliches Seminar (Scientific Seminar) for Graduate Students |
| Instructors: | 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. |
Robot Learning and Control Project Course
| Terms Offered: | Summer 2023 |
| Target Audience: | Projektpraktikum (Project Internship) for Graduate Students |
| Instructors: | Prof. Angela Schoellig |
| Topics Covered: | Students will gain hands-on experience in robot learning and control by developing their own comprehensive hardware/software solutions for a given robotics problem. Topics will vary each term. Student teams work jointly on the hardware and software solutions 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. |
Courses at University of Toronto
Undergraduate
ROB310: Mathematics for Robotics
| Terms Offered: | Fall 2015-20 |
| Target Audience: | Third-year undergraduate course, Engineering Science |
| Instructors: | 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 |
