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Online Course on Autonomous Navigation for Flying Robots

In the continuation of its online courses edX with Technical University of Munich is offering free online course “Autonomous Navigation for Flying Robots”.

In recent years, flying robots such as miniature helicopters or quadrotors have received a large gain in popularity. Potential applications range from aerial filming over remote visual inspection to automatic 3D reconstruction of buildings. Navigating a quadrotor manually requires a skilled pilot and constant concentration. Therefore, there is a strong scientific interest to develop solutions that enable quadrotors to fly autonomously and without constant human supervision. This is a challenging research problem because the payload of a quadrotor is uttermost constrained and so both the quality of the onboard sensors and the available computing power is strongly limited.

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The course on Autonomous Navigation will introduce the basic concepts for autonomous navigation with quadrotors, including topics such as probabilistic state estimation, linear control and path planning.

with the help of this course the applicants will learn how to infer the position of the quadrotor from its sensor readings, how to navigate along a series of waypoints and how to plan collision free trajectories.

The course consists of weekly video lectures with quizzes and hands-on programming tasks. The programming exercises will require you to write small code snippets in Python to make a quadrotor fly in simulation.

This course is drafted for graduate students in computer science, electrical engineering or mechanical engineering. The course is based on the TUM lecture “Visual Navigation for Flying Robots” which received the TUM TeachInf best lecture award in 2012 and 2013.

Course Date & Duration

This online course will start from 6th May 2014 for the duration of 8 weeks. Students need to spend 4 hours/week on this course.

Eligibility Criteria

To pursue this course students are recommend to have solid background in linear algebra and 3D geometry. The programming exercises will require to write small code snippets in Python to make a quadrotor fly in simulation.

Course Staff

Jürgen Sturm is a postdoctoral researcher in the Computer Vision group at the Technische Universität München.

Daniel Cremers holds the chair for Computer Vision and Pattern Recognition at the Technische Universität München.

Christian Kerl is a PhD student in the Computer Vision group at the Technische Universität München.

Julian Tatsch is a master student in computer science at the Technische Universität München.

Jonas Jelten is a bachelor student in computer science at the Technische Universität München.

For more information, visit the edX official link