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Masterpraktikum - Intelligent Mobile Robots with ROS (IN2106, IN4290)

Course 0000002736 in WS 2020/1

General Data

Course Type practical training
Semester Weekly Hours 6 SWS
Organisational Unit Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems (Prof. Knoll)
Lecturers Robin Dietrich
Alexander Lenz
Responsible/Coordination: Alois Christian Knoll
Dates 1 singular or moved dates

Assignment to Modules

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks <b>Important:</b> There will be an online kick-off meeting held on July 14th at 4 pm using zoom. Please attend this meeting if you are interested in this course. Meeting Link: https://tum-conf.zoom.us/j/92083728698 Meeting ID: 920 8372 8698 Password: 826135 Autonomous mobile robots have been a research area of interest for decades now. They have come a long way from first navigation approaches using large, single-core computers and ultra-sound sensors to fully autonomous machines equipped with GPUs and advances sensors like 3D lidars. Nowadays, they are frequently used in logistic centers, healthcare system or department stores. They are able to operate safely and autonomously in their environment as well as detect and interact with people. In this course, students will get the chance to understand all parts of a mobile robot (software & hardware) and work on their own, self-chosen project on a real mobile robot (Robotino) equipped with multiple different sensors. This course attempts to give a practically oriented overview of all disciplines with the field of mobile robotics. This includes the localization, mapping, navigation and perception of the robot in an (un-)known environment. In order to master this knowledge, the first part of the course will be consisting of (online) lectures, each focusing on one of the previously mentioned disciplines. At the end of each lecture the student has to work on a small practical exercise in order to apply the theoretical knowledge in the real (simulated) world. During the second part of the course, students will form heterogeneous teams of 3-5 members, preferably with different backgrounds. Each team will then choose a problem or task to work on freely. This task could be almost anything, from developing a delivery robot (more software oriented) to trying to solve a known problem (e.g. localization) with a new algorithm (e.g. spiking neural networks) (more research oriented). This allows the students to choose a topic aligned with their personal interests and knowledge. Due to Corona restrictions, the first part of the course will most likely be held completely virtual, including virtual lectures and exercises using a simulator. The second part, however, will definitely take place in the lab at Hochbrück where you can pick one of multiple Robotino robots for your final project. Since the final project is team based, this course is suitable for students with almost any kind of background. As long as you are interested in mobile robots and motivated to work in a team on an actual robot to solve a problem, you are going to fit right in. (Of course you need to have some kind of programming experience, see next paragraph)
Links E-Learning course (e. g. Moodle)
TUMonline entry
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