Roland Siegwart: Catalogue data in Spring Semester 2018

Name Prof. Dr. Roland Siegwart
FieldAutonome Systeme
Address
Inst. f. Robotik u. Intell. Syst.
ETH Zürich, LEE J 205
Leonhardstrasse 21
8092 Zürich
SWITZERLAND
Telephone+41 44 632 23 58
Fax+41 44 632 11 81
E-mailrsiegwart@ethz.ch
DepartmentMechanical and Process Engineering
RelationshipFull Professor

NumberTitleECTSHoursLecturers
151-0073-11LIndoor Mobility Robot
Prerequisite: Enrollment for 151-0073-10L Indoor Mobility Robot in HS17.
14 credits15AR. Siegwart
AbstractStudents develop and build a product from A-Z! They work in teams and independently, learn to structure problems, to identify solutions, system analysis and simulations, as well as presentation and documentation techniques. They build the product with access to a machine shop and state of the art engineering tools (Matlab, Simulink, etc).
ObjectiveThe various objectives of the Focus Project are:
- Synthesizing and deepening the theoretical knowledge from the basic courses of the 1. - 4. semester
- Team organization, work in teams, increase of interpersonal skills
- Independence, initiative, independent learning of new topic contents
- Problem structuring, solution identification in indistinct problem definitions, searches of information
- System description and simulation
- Presentation methods, writing of a document
- Ability to make decisions, implementation skills
- Workshop and industrial contacts
- Learning and recess of special knowledge
- Control of most modern engineering tools (Matlab, Simulink, CAD, CAE, PDM)
151-0073-21LRobotic Elephant Trunk
Prerequisite: Enrollment for 151-0073-20L Robotic Elephant Trunk in HS17.
14 credits15AM. Hutter, R. Siegwart
AbstractStudents develop and build a product from A-Z! They work in teams and independently, learn to structure problems, to identify solutions, system analysis and simulations, as well as presentation and documentation techniques. They build the product with access to a machine shop and state of the art engineering tools (Matlab, Simulink, etc).
ObjectiveThe various objectives of the Focus Project are:
- Synthesizing and deepening the theoretical knowledge from the basic courses of the 1. - 4. semester
- Team organization, work in teams, increase of interpersonal skills
- Independence, initiative, independent learning of new topic contents
- Problem structuring, solution identification in indistinct problem definitions, searches of information
- System description and simulation
- Presentation methods, writing of a document
- Ability to make decisions, implementation skills
- Workshop and industrial contacts
- Learning and recess of special knowledge
- Control of most modern engineering tools (Matlab, Simulink, CAD, CAE, PDM)
151-0623-00LETH Zurich Distinguished Seminar in Robotics, Systems and Controls Information
Students for other Master's programmes in Department Mechanical and Process Engineering cannot use the credit in the category Core Courses
1 credit1SB. Nelson, M. Chli, R. Gassert, M. Hutter, W. Karlen, R. Riener, R. Siegwart
AbstractThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
ObjectiveObtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see http://www.msrl.ethz.ch/education/distinguished-seminar-in-robotics--systems---controls--151-0623-0.html for a list of upcoming lectures.
ContentThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls. MSc students in Robotics, Systems, and Controls are required to attend every lecture. Attendance will be monitored. If for some reason a student cannot attend one of the lectures, the student must select another ETH or University of Zurich seminar related to the field and submit a one page description of the seminar topic. Please see http://www.msrl.ethz.ch/education/distinguished-seminar-in-robotics--systems---controls--151-0623-0.html for a suggestion of other lectures.
Prerequisites / NoticeStudents are required to attend all seven lectures to obtain credit. If a student must miss a lecture then attendance at a related special lecture will be accepted that is reported in a one page summary of the attended lecture. No exceptions to this rule are allowed.
151-0634-00LPerception and Learning for Robotics
Number of participants limited to: 30

To apply for the course please create a CV in pdf of max. 2 pages, including your machine learning and/or robotics experience. Please send the pdf to cesarc@ethz.ch for approval.
4 credits1AC. D. Cadena Lerma, I. Gilitschenski, R. Siegwart
AbstractThis course covers tools from statistics and machine learning enabling the participants to deploy these algorithms as building blocks for perception pipelines on robotic tasks. All mathematical methods provided within the course will be discussed in context of and motivated by example applications mostly from robotics. The main focus of this course are student projects on robotics.
ObjectiveApplying Machine Learning methods for solving real-world robotics problems.
ContentDeep Learning for Perception; (Deep) Reinforcement Learning; Graph-Based Simultaneous Localization and Mapping
Lecture notesSlides will be made available to the students.
LiteratureWill be announced in the first lecture.
Prerequisites / NoticeThe students are expected to be familiar with material of the "Recursive Estimation" and the "Learning and Intelligent Systems" lectures. Particularly understanding of basic machine learning concepts, stochastic gradient descent for neural networks, reinforcement learning basics, and knowledge of Bayesian Filtering are required. Furtheremore, good knowledge of programming in C++ and Python is required.
151-0854-00LAutonomous Mobile Robots Information 5 credits4GR. Siegwart, M. Chli, J. Nieto
AbstractThe 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, envionmen perception, and probabilistic environment modeling, localizatoin, mapping and navigation. Theory will be deepened by exercises with small mobile robots and discussed accross application examples.
ObjectiveThe 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, envionmen perception, and probabilistic environment modeling, localizatoin, mapping and navigation.
Lecture notesThis 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.
LiteratureThis 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
401-5860-00LSeminar in Robotics for CSE4 credits2SR. Siegwart
AbstractThis course provides an opportunity to familiarize yourself with the advanced topics of robotics and mechatronics research. The seminar consists of a literature study, including a report and a presentation.
ObjectiveThe students are familiar with the challenges of the fascinating and interdisciplinary field of Robotics and Mechatronics. They are introduced in the basics of independent non-experimental scientific research and are able to summarize and to present the results efficiently.
ContentThis 4 ECTS course requires each student to discuss a study plan with the lecturer and select minimum 10 relevant scientific publications to read through. At the end of semester, the results should be presented in an oral presentation and summarized in a report.