Number | Title | ECTS | Hours | Lecturers |
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151-0854-00L | Autonomous Mobile Robots | 5 credits | 4G | R. Siegwart,
M. Chli,
N. Lawrance |
Abstract | The objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, environment perception, and probabilistic environment modeling, localizatoin, mapping and navigation. Theory will be deepened by exercises with small mobile robots and discussed accross application examples. |
Objective | The objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, environment perception, and probabilistic environment modeling, localizatoin, mapping and navigation. |
Lecture notes | This lecture is enhanced by around 30 small videos introducing the core topics, and multiple-choice questions for continuous self-evaluation. It is developed along the TORQUE (Tiny, Open-with-Restrictions courses focused on QUality and Effectiveness) concept, which is ETH's response to the popular MOOC (Massive Open Online Course) concept. |
Literature | This lecture is based on the Textbook: Introduction to Autonomous Mobile Robots Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, Second Edition 2011, ISBN: 978-0262015356 |
151-9062-00L | Robotics Summer School Number of participants limited to 30. Students need to apply here: Link | 1 credit | 2S | C. D. Cadena Lerma,
M. Chli,
M. Hutter |
Abstract | This summer school offers lectures and hands-on tutorials on fundamental concepts that every roboticist around the world should possess. The tutorials as well as hands-on sessions with cutting edge robotics platforms will take place at a dedicated education and training center for search and rescue. |
Objective | Practical robotics application of fundamental concepts of state estimation, control and navigation. |
Content | Trajectory Optimization; State Estimation; Localization and Mapping with multiple sensor modalities; Obstacle Avoidance and Path Planning; Recognition and Tracking. |
Prerequisites / Notice | C++ programming basics, Linux Basics. Students need to bring their own laptop to the summer school. Instructions how to prepare the laptop are provided on the summer school homepage one week prior to the start. Students are expected to have taken the "151-0662-00L Programming for Robotics - Introduction to ROS" lecture or have acquired equivalent knowledge of ROS. |