Search result: Catalogue data in Autumn Semester 2016
|Mechanical Engineering Master|
|Robotics, Systems and Control|
|151-0104-00L||Uncertainty Quantification for Engineering & Life Sciences |
Does not take place this semester.
Number of participants limited to 60.
|W||4 credits||3G||P. Koumoutsakos|
|Abstract||Quantification of uncertainties in computational models pertaining to applications in engineering and life sciences. Exploitation of massively available data to develop computational models with quantifiable predictive capabilities. Applications of Uncertainty Quantification and Propagation to problems in mechanics, control, systems and cell biology.|
|Objective||The course will teach fundamental concept of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences. Emphasis will be placed on practical and computational aspects of UQ+P including the implementation of relevant algorithms in multicore architectures.|
|Content||Topics that will be covered include: Uncertainty quantification under|
parametric and non-parametric modelling uncertainty, Bayesian inference with model class assessment, Markov Chain Monte Carlo simulation, prior and posterior reliability analysis.
|Lecture notes||The class will be largely based on the book: Data Analysis: A Bayesian Tutorial by Devinderjit Sivia as well as on class notes and related literature that will be distributed in class.|
|Literature||1. Data Analysis: A Bayesian Tutorial by Devinderjit Sivia |
2. Probability Theory: The Logic of Science by E. T. Jaynes
3. Class Notes
|Prerequisites / Notice||Fundamentals of Probability, Fundamentals of Computational Modeling|
|151-0107-20L||High Performance Computing for Science and Engineering (HPCSE) I||W||4 credits||4G||M. Troyer, P. Chatzidoukas|
|Abstract||This course gives an introduction into algorithms and numerical methods for parallel computing for multi and many-core architectures and for applications from problems in science and engineering.|
|Objective||Introduction to HPC for scientists and engineers|
1. Parallel Computing Architectures
|Content||Programming models and languages:|
1. C++ threading (2 weeks)
2. OpenMP (4 weeks)
3. MPI (5 weeks)
Computers and methods:
1. Hardware and architectures
3. Particles: N-body solvers
4. Fields: PDEs
5. Stochastics: Monte Carlo
Class notes, handouts
|151-0532-00L||Nonlinear Dynamics and Chaos I||W||4 credits||2V + 2U||G. Haller, F. Kogelbauer|
|Abstract||Basic facts about nonlinear systems; stability and near-equilibrium dynamics; bifurcations; dynamical systems on the plane; non-autonomous dynamical systems; chaotic dynamics.|
|Objective||This course is intended for Masters and Ph.D. students in engineering sciences, physics and applied mathematics who are interested in the behavior of nonlinear dynamical systems. It offers an introduction to the qualitative study of nonlinear physical phenomena modeled by differential equations or discrete maps. We discuss applications in classical mechanics, electrical engineering, fluid mechanics, and biology. A more advanced Part II of this class is offered every other year.|
|Content||(1) Basic facts about nonlinear systems: Existence, uniqueness, and dependence on initial data.|
(2) Near equilibrium dynamics: Linear and Lyapunov stability
(3) Bifurcations of equilibria: Center manifolds, normal forms, and elementary bifurcations
(4) Nonlinear dynamical systems on the plane: Phase plane techniques, limit sets, and limit cycles.
(5) Time-dependent dynamical systems: Floquet theory, Poincare maps, averaging methods, resonance
|Lecture notes||The class lecture notes will be posted electronically after each lecture. Students should not rely on these but prepare their own notes during the lecture.|
|Prerequisites / Notice||- Prerequisites: Analysis, linear algebra and a basic course in differential equations.|
- Exam: two-hour written exam in English.
- Homework: A homework assignment will be due roughly every other week. Hints to solutions will be posted after the homework due dates.
|151-0563-01L||Dynamic Programming and Optimal Control||W||4 credits||2V + 1U||R. D'Andrea|
|Abstract||Introduction to Dynamic Programming and Optimal Control.|
|Objective||Covers the fundamental concepts of Dynamic Programming & Optimal Control.|
|Content||Dynamic Programming Algorithm; Deterministic Systems and Shortest Path Problems; Infinite Horizon Problems, Bellman Equation; Deterministic Continuous-Time Optimal Control.|
|Literature||Dynamic Programming and Optimal Control by Dimitri P. Bertsekas, Vol. I, 3rd edition, 2005, 558 pages, hardcover.|
|Prerequisites / Notice||Requirements: Knowledge of advanced calculus, introductory probability theory, and matrix-vector algebra.|
|151-0567-00L||Engine Systems||W||4 credits||3G||C. Onder|
|Abstract||Introduction to current and future engine systems and their control systems|
|Objective||Introduction to methods of control and optimization of dynamic systems. Application to real engines. Understand the structure and behavior of drive train systems and their quantitative descriptions.|
|Content||Physical description and mathematical models of components and subsystems (mixture formation, load control, supercharging, emissions, drive train components, etc.).|
Case studies of model-based optimal design and control of engine systems with the goal of minimizing fuel consumption and emissions.
|Lecture notes||Introduction to Modeling and Control of Internal Combustion Engine Systems|
Guzzella Lino, Onder Christopher H.
2010, Second Edition, 354 p., hardbound
|Prerequisites / Notice||Combined homework and testbench exercise (air-to-fuel-ratio control or idle-speed control) in groups|
|151-0569-00L||Vehicle Propulsion Systems||W||4 credits||3G||C. Onder, P. Elbert|
|Abstract||Introduction to current and future propulsion systems and the electronic control of their longitudinal behavior|
|Objective||Introduction to methods of system optimization and controller design for vehicles. Understanding the structure and working principles of conventional and new propulsion systems. Quantitative descriptions of propulsion systems|
|Content||Understanding of physical phenomena and mathematical models of components and subsystems (manual, automatic and continuously variable transmissions, energy storage systems, electric drive trains, batteries, hybrid systems, fuel cells, road/wheel interaction, automatic braking systems, etc.).|
Presentation of mathematical methods, CAE tools and case studies for the model-based design and control of propulsion systems with the goal of minimizing fuel consumption and emissions.
|Lecture notes||Vehicle Propulsion Systems --|
Introduction to Modeling and Optimization
Guzzella Lino, Sciarretta Antonio
2013, X, 409 p. 202 illus., Geb.
|Prerequisites / Notice||Lectures of Dr. Ch. Onder are also possible to be held in German|
|151-0573-00L||System Modeling||W||4 credits||2V + 2U||G. Ducard, C. Onder|
|Abstract||Generic modeling approaches for control-oriented models based on first principles, Lagrangian formalism and experimental data. Model parametrization and estimation techniques. Analysis of linear systems, model scaling, linearization, order reduction, and balancing. Basic analysis of nonlinear models.|
|Objective||Introduction to system modeling for control. Parameter identification. Analysis of linear and nonlinear systems. Case studies.|
|Content||Introduction to generic system modeling approaches for control-oriented models based on first principles and on experimental data. |
Examples: mechatronic, thermodynamic, chemistry, fluid dynamic, energy, and process engineering systems. Model scaling, linearization, order reduction, and balancing. Estimation techniques (least-squares methods).
Class case studies: Loud-speaker, Water-propelled rocket, geostationary satellites, etc.
The exercises address practical examples. One larger case study is to be solved.
|Lecture notes||The handouts in English will be sold in the first lecture.|
|Literature||A list of references is included in the handouts.|
|151-0593-00L||Embedded Control Systems||W||4 credits||6G||J. S. Freudenberg, M. Schmid Daners, C. Onder|
|Abstract||This course provides a comprehensive overview of embedded control systems. The concepts introduced are implemented and verified on a microprocessor-controlled haptic device.|
|Objective||Familiarize students with main architectural principles and concepts of embedded control systems.|
|Content||An embedded system is a microprocessor used as a component in another piece of technology, such as cell phones or automobiles. In this intensive two-week block course the students are presented the principles of embedded digital control systems using a haptic device as an example for a mechatronic system. A haptic interface allows for a human to interact with a computer through the sense of touch.|
Subjects covered in lectures and practical lab exercises include:
- The application of C-programming on a microprocessor
- Digital I/O and serial communication
- Quadrature decoding for wheel position sensing
- Queued analog-to-digital conversion to interface with the analog world
- Pulse width modulation
- Timer interrupts to create sampling time intervals
- System dynamics and virtual worlds with haptic feedback
- Introduction to rapid prototyping
|Lecture notes||Lecture notes, lab instructions, supplemental material|
|Prerequisites / Notice||Prerequisite courses are Control Systems I and Informatics I.|
This course is restricted to 33 students due to limited lab infrastructure. Interested students please contact Marianne Schmid (E-Mail: firstname.lastname@example.org)
After your reservation has been confirmed please register online at www.mystudies.ethz.ch.
Detailed information can be found on the course website
|151-0601-00L||Theory of Robotics and Mechatronics||W||4 credits||3G||P. Korba, S. Stoeter, B. Nelson|
|Abstract||This course provides an introduction and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control. It’s a requirement for the Robotics Vertiefung and for the Masters in Mechatronics and Microsystems.|
|Objective||Robotics is often viewed from three perspectives: perception (sensing), manipulation (affecting changes in the world), and cognition (intelligence). Robotic systems integrate aspects of all three of these areas. This course provides an introduction to the theory of robotics, and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control. This course is a requirement for the Robotics Vertiefung and for the Masters in Mechatronics and Microsystems.|
|Content||An introduction to the theory of robotics, and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control.|
|Prerequisites / Notice||The course will be taught in English.|
Does not take place this semester.
|W||4 credits||3G||B. Nelson|
|Abstract||Microrobotics is an interdisciplinary field that combines aspects of robotics, micro and nanotechnology, biomedical engineering, and materials science. The aim of this course is to expose students to the fundamentals of this emerging field. Throughout the course students are expected to submit assignments. The course concludes with an end-of-semester examination.|
|Objective||The objective of this course is to expose students to the fundamental aspects of the emerging field of microrobotics. This includes a focus on physical laws that predominate at the microscale, technologies for fabricating small devices, bio-inspired design, and applications of the field.|
|Content||Main topics of the course include:|
- Scaling laws at micro/nano scales
- Low Reynolds number flows
- Observation tools
- Materials and fabrication methods
- Applications of biomedical microrobots
|Lecture notes||The powerpoint slides presented in the lectures will be made available in hardcopy and as pdf files. Several readings will also be made available electronically.|
|Prerequisites / Notice||The lecture will be taught in English.|
|151-0623-00L||ETH Zurich Distinguished Seminar in Robotics, Systems and Controls |
Students for other Master's programmes in Department Mechanical and Process Engineering cannot use the credit in the category Core Courses
|W||1 credit||1S||B. Nelson, J. Buchli, M. Chli, R. Gassert, M. Hutter, W. Karlen, R. Riener, R. Siegwart|
|Abstract||This course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.|
|Objective||Obtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see Link for a list of upcoming lectures.|
|Content||This 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 Link for a suggestion of other lectures.|
|Prerequisites / Notice||Students 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.|
|151-0632-00L||Vision Algorithms for Mobile Robotics |
Number of participants limited to 50
|W||4 credits||2V + 2U||D. Scaramuzza|
|Abstract||For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the fundamental computer vision algorithms used in mobile robotics, in particular: feature extraction, multiple view geometry, dense reconstruction, object tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithm behind Google Tango).|
|Objective||Learn the fundamental computer vision algorithms used in mobile robotics, in particular: feature extraction, multiple view geometry, dense reconstruction, object tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithm behind Google Tango).|
|Content||For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the fundamental computer vision algorithms used in mobile robotics, in particular: feature extraction, multiple view geometry, dense reconstruction, object tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithm behind Google Tango).|
|Lecture notes||Lecture slides will be available after each lecture on the course official website: http://rpg.ifi.uzh.ch/teaching.html|
|Literature|| Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010. |
 Robotics Vision and Control: Fundamental Algorithms, by Peter Corke 2011.
|Prerequisites / Notice||Basics of algebra and geomertry, matrix calculus.|
|151-0655-00L||Skills for Creativity and Innovation||W||4 credits||3G||I. Goller, C. Kobe, M. Meboldt|
|Abstract||This lecture aims to enhance the knowledge and competency of students regarding their innovation capability. An overview on prerequisites of and different skills for creativity and innovation in individual & team settings is given. The focus of this lecture is clearly on building competencies - not just acquiring knowledge.|
|Objective||- Basic knowledge about creativity and skills|
- Knowledge about individual prerequisites for creativity
- Development of individual skills for creativity
- Knowledge about teams
- Development of team-oriented skills for creativity
- Knowledge and know-how about transfer to idea generation teams
|Content||Basic knowledge about creativity and skills:|
- Introduction into creativity & innovation: definitions and models
Knowledge about individual prerequisites for creativity:
- Personality, motivation, intelligence
Development of individual skills for creativity:
- Focus on creativity as problem analysis & solving
- Individual skills in theoretical models
- Individual competencies: exercises and reflection
Knowledge about teams:
- Definitions and models
- Roles in innovation processes
Development of team-oriented skills for creativity:
- Idea generation and development in teams
- Cooperation & communication in innovation teams
Knowledge and know-how about transfer to idea generation teams:
- Self-reflection & development planning
- Methods of knowledge transfer
|Lecture notes||Slides, script and other documents will be distributed via moodle.ethz.ch|
(access only for students registered to this course)
|Literature||Please refer to lecture script.|
|151-0727-00L||Colloquium on Manufacturing Technology||W||4 credits||3K||K. Wegener, F. Kuster|
|Abstract||Future training on selected current topics of the manufacturing technology. Per afternoon a selected topic is presented in several lectures, by the majority by experts from the industry. The students prepare a summary of the lectures given and prepare themselves on the basis of these lectures and own information search.|
|Objective||Contious further training to current topics of the manufacturing technique. Exchange of experience and knowledge with the industry and other universities.|
|Content||Selected actual topics on manufacturing methods and tools, machine tools, NC-control and drives, components and measuring methods and devices. Topics are changing every year.|
|Lecture notes||no Script|
|Prerequisites / Notice||- Students must have participated and passed the courses Manufacturing, Production Machines I and Forming Technology III - Forming Processes.|
- Further training with specialized lectures and large participation from the industry.
Language: Help for English speaking students on request.
|151-0851-00L||Robot Dynamics||W||4 credits||2V + 1U||M. Hutter, R. Siegwart, T. Stastny|
|Abstract||We will provide an overview on how to kinematically and dynamically model typical robotic systems such as robot arms, legged robots, rotary wing systems, or fixed wing.|
|Objective||The primary objective of this course is that the student deepens an applied understanding of how to model the most common robotic systems. The student receives a solid background in kinematics, dynamics, and rotations of multi-body systems. On the basis of state of the art applications, he/she will learn all necessary tools to work in the field of design or control of robotic systems.|
|Content||The course consists of three parts: First, we will refresh and deepen the student's knowledge in kinematics, dynamics, and rotations of multi-body systems. In this context, the learning material will build upon the courses for mechanics and dynamics available at ETH, with the particular focus on their application to robotic systems. The goal is to foster the conceptual understanding of similarities and differences among the various types of robots. In the second part, we will apply the learned material to classical robotic arms as well as legged systems and discuss kinematic constraints and interaction forces. In the third part, focus is put on modeling fixed wing aircraft, along with related design and control concepts. In this context, we also touch aerodynamics and flight mechanics to an extent typically required in robotics. The last part finally covers different helicopter types, with a focus on quadrotors and the coaxial configuration which we see today in many UAV applications. Case studies on all main topics provide the link to real applications and to the state of the art in robotics.|
|Prerequisites / Notice||The contents of the following ETH Bachelor lectures or equivalent are assumed to be known: Mechanics and Dynamics, Control, Basics in Fluid Dynamics.|
|151-0917-00L||Mass Transfer||W||4 credits||2V + 2U||R. Büchel, S. E. Pratsinis|
|Abstract||This course presents the fundamentals of transport phenomena with emphasis on mass transfer. The physical significance of basic principles is elucidated and quantitatively described. Furthermore the application of these principles to important engineering problems is demonstrated.|
|Objective||This course presents the fundamentals of transport phenomena with emphasis on mass transfer. The physical significance of basic principles is elucidated and quantitatively described. Furthermore the application of these principles to important engineering problems is demonstrated.|
|Content||Fick's laws; application and significance of mass transfer; comparison of Fick's laws with Newton's and Fourier's laws; derivation of Fick's 2nd law; diffusion in dilute and concentrated solutions; rotating disk; dispersion; diffusion coefficients, viscosity and heat conduction (Pr and Sc numbers); Brownian motion; Stokes-Einstein equation; mass transfer coefficients (Nu and Sh numbers); mass transfer across interfaces; Reynolds- and Chilton-Colburn analogies for mass-, heat-, and momentum transfer in turbulent flows; film-, penetration-, and surface renewal theories; simultaneous mass, heat and momentum transfer (boundary layers); homogenous and heterogenous reversible and irreversible reactions; diffusion-controlled reactions; mass transfer and first order heterogenous reaction. Applications.|
|Literature||Cussler, E.L.: "Diffusion", 2nd edition, Cambridge University Press, 1997.|
|Prerequisites / Notice||Two tests are offered for practicing the course material. Participation is mandatory.|
|151-1116-00L||Introduction to Aircraft and Car Aerodynamics||W||4 credits||3G||J. Wildi|
|Abstract||Aircraft aerodynamics: Atmosphere; aerodynamic forces (lift, drag); thrust.|
Vehicle aerodynamics: Aerodynamic and mass forces, drag, lift, car aerodynamics and performence. Passenger cars, trucks, racing cars.
|Objective||An introduction to the basic principles and interrelationships of aircraft and automotive aerodynamics.|
To understand the basic relations of the origin of aerodynamic forces (ie lift, drag). To quantify the aerodynamic forces for basic configurations of aercraft and car components.
Illustration of the intrinsic problems and results using examples.
Using experimental and theoretical methods to illustrate possibilities and limits.
|Content||Aircraft aerodynamics: atmosphere, aerodynamic forces (ascending force: profile, wings. Resistance, residual resistance, induced resistance); thrust (overview of the propulsion system, aerodynamics of the propellers), introduction to static longitudinal stability.|
Automobile aerodynamics: Basic principles: aerodynamic force and the force of inertia, resistance, drive, aerodynamic and driving performance. Cars commercial vehicles, racing cars.
|Lecture notes||1.) Grundlagen der Flugtechnik (Basics of flight science, script in german language)|
2.) Einführung in die Fahrzeugaerodynamik (Introduction in car aerodynamics, script in german language)
|Literature||English literature covering the content of the course:|
- Anderson Jr, John D: Introduction to Flight, Mc Graw Hill, Ed 06, 2007; ISBN: 9780073529394
- Mc Cormick, B.W.: Aerodynamics, Aeronautics and Flight Mechanics, John Wiley and Sons, 1979
- Hucho, Wolf-Heinrich: Aerodynamics of Road Vehicles, SAE International, 1998
|227-0225-00L||Linear System Theory||W||6 credits||5G||M. Kamgarpour|
|Abstract||The class is intended to provide a comprehensive overview of the theory of linear dynamical systems, their use in control, filtering, and estimation and their applications to areas ranging from avionics to systems biology.|
|Objective||By the end of the class students should be comfortable with the fundamental results in linear system theory and the mathematical tools used to derive them.|
|Content||- Rings, fields and linear spaces, normed linear spaces and inner product spaces.|
- Ordinary differential equations, existence and uniqueness of solutions.
- Continuous and discrete time, time varying linear systems. Time domain solutions. Time invariant systems treated as a special case.
- Controllability and observability, canonical forms, Kalman decomposition. Time invariant systems treated as a special case.
- Stability and stabilization, observers, state and output feedback, separation principle.
- Realization theory.
|Lecture notes||F.M. Callier and C.A. Desoer, "Linear System Theory", Springer-Verlag, 1991.|
|Prerequisites / Notice||Prerequisites: Control Systems I (227-0103-00) or equivalent and sufficient mathematical maturity.|
|227-0447-00L||Image Analysis and Computer Vision||W||6 credits||3V + 1U||L. Van Gool, O. Göksel, E. Konukoglu|
|Abstract||Light and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation and deformable shape matching. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition.|
|Objective||Overview of the most important concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises.|
|Content||The first part of the course starts off from an overview of existing and emerging applications that need computer vision. It shows that the realm of image processing is no longer restricted to the factory floor, but is entering several fields of our daily life. First it is investigated how the parameters of the electromagnetic waves are related to our perception. Also the interaction of light with matter is considered. The most important hardware components of technical vision systems, such as cameras, optical devices and illumination sources are discussed. The course then turns to the steps that are necessary to arrive at the discrete images that serve as input to algorithms. The next part describes necessary preprocessing steps of image analysis, that enhance image quality and/or detect specific features. Linear and non-linear filters are introduced for that purpose. The course will continue by analyzing procedures allowing to extract additional types of basic information from multiple images, with motion and depth as two important examples. The estimation of image velocities (optical flow) will get due attention and methods for object tracking will be presented. Several techniques are discussed to extract three-dimensional information about objects and scenes. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed.|
|Lecture notes||Course material Script, computer demonstrations, exercises and problem solutions|
|Prerequisites / Notice||Prerequisites: |
Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on Linux and C.
The course language is English.
|227-0517-00L||Electrical Drive Systems II||W||6 credits||4G||P. Steimer, G. Scheuer, C. A. Stulz|
|Abstract||In the course "Drive System II" the power semiconductors are repeated. The creation of converters based on the combination of switches/cells and based topologies is explained. Another main focus is on the 3-level inverter with its switching and transfer functions. Further topics are the control of the synchronous machine, of line-side converters and issues with converter-fed machines|
|Objective||The students establish a deeper understanding in regards of the design of the main components of an electrical drive system. They establish knowledge on the most important interaction with the grid and the machine and their related high dynamic control.|
|Content||Converter topologies (switch or cell based), multi-pulse diode rectifiers, system aspects of transfomer and electrical machines, 3-level inverter with its switching and transfer functions, grid side harmonics, modeling and control of synchronous machines (including permanent magnet machines), control of line-side converters, reflection effects with power cables, winding isolation and bearing stress. Field trip to ABB Semionductors.|
|Lecture notes||Skript is sold at the beginning of the lectures or can be downloaded from Ilias|
|Literature||Skript of lecture; References in skript to related technical publications and books|
|Prerequisites / Notice||Prerequisites: Electrical Drive Systems I (recommended), Basics in electrical engineering, power electronics, automation and mechatronics|
|227-0689-00L||System Identification||W||4 credits||2V + 1U||R. Smith|
|Abstract||Theory and techniques for the identification of dynamic models from experimentally obtained system input-output data.|
|Objective||To provide a series of practical techniques for the development of dynamical models from experimental data, with the emphasis being on the development of models suitable for feedback control design purposes. To provide sufficient theory to enable the practitioner to understand the trade-offs between model accuracy, data quality and data quantity.|
|Content||Introduction to modeling: Black-box and grey-box models; Parametric and non-parametric models; ARX, ARMAX (etc.) models.|
Predictive, open-loop, black-box identification methods. Time and frequency domain methods. Subspace identification methods.
Optimal experimental design, Cramer-Rao bounds, input signal design.
Parametric identification methods. On-line and batch approaches.
Closed-loop identification strategies. Trade-off between controller performance and information available for identification.
|Literature||"System Identification; Theory for the User" Lennart Ljung, Prentice Hall (2nd Ed), 1999.|
"Dynamic system identification: Experimental design and data analysis", GC Goodwin and RL Payne, Academic Press, 1977.
|Prerequisites / Notice||Control systems (227-0216-00L) or equivalent.|
|227-0920-00L||Seminar in Systems and Control||Z||0 credits||1S||F. Dörfler, R. D'Andrea, J. Lygeros, R. Smith|
|Abstract||Current topics in Systems and Control presented mostly by external speakers from academia and industry|
|252-3110-00L||Human Computer Interaction||W||4 credits||2V + 1U||O. Hilliges, M. Norrie|
|Abstract||The course provides an introduction to the field of human-computer interaction, emphasising the central role of the user in system design. Through detailed case studies, students will be introduced to different methods used to analyse the user experience and shown how these can inform the design of new interfaces, systems and technologies.|
|Objective||The goal of the course is that students should understand the principles of user-centred design and be able to apply these in practice.|
|Content||The course will introduce students to various methods of analysing the user experience, showing how these can be used at different stages of system development from requirements analysis through to usability testing. Students will get experience of designing and carrying out user studies as well as analysing results. The course will also cover the basic principles of interaction design. Practical exercises related to touch and gesture-based interaction will be used to reinforce the concepts introduced in the lecture. To get students to further think beyond traditional system design, we will discuss issues related to ambient information and awareness.|
|263-5210-00L||Probabilistic Artificial Intelligence||W||4 credits||2V + 1U||S. Tschiatschek|
|Abstract||This course introduces core modeling techniques and algorithms from statistics, optimization, planning, and control and study applications in areas such as sensor networks, robotics, and the Internet.|
|Objective||How can we build systems that perform well in uncertain environments and unforeseen situations? How can we develop systems that exhibit "intelligent" behavior, without prescribing explicit rules? How can we build systems that learn from experience in order to improve their performance? We will study core modeling techniques and algorithms from statistics, optimization, planning, and control and study applications in areas such as sensor networks, robotics, and the Internet. The course is designed for upper-level undergraduate and graduate students.|
- Search (BFS, DFS, A*), constraint satisfaction and optimization
- Tutorial in logic (propositional, first-order)
- Bayesian Networks (models, exact and approximative inference, learning) - Temporal models (Hidden Markov Models, Dynamic Bayesian Networks)
- Probabilistic palnning (MDPs, POMPDPs)
- Reinforcement learning
- Combining logic and probability
|Prerequisites / Notice||Solid basic knowledge in statistics, algorithms and programming|
|263-5902-00L||Computer Vision||W||6 credits||3V + 1U + 1A||L. Van Gool, V. Ferrari, A. Geiger|
|Abstract||The goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.|
|Objective||The objectives of this course are:|
1. To introduce the fundamental problems of computer vision.
2. To introduce the main concepts and techniques used to solve those.
3. To enable participants to implement solutions for reasonably complex problems.
4. To enable participants to make sense of the computer vision literature.
|Content||Camera models and calibration, invariant features, Multiple-view geometry, Model fitting, Stereo Matching, Segmentation, 2D Shape matching, Shape from Silhouettes, Optical flow, Structure from motion, Tracking, Object recognition, Object category recognition|
|Prerequisites / Notice||It is recommended that students have taken the Visual Computing lecture or a similar course introducing basic image processing concepts before taking this course.|
|376-1219-00L||Rehabilitation Engineering II: Rehabilitation of Sensory and Vegetative Functions||W||3 credits||2V||R. Riener, R. Gassert, L. Marchal Crespo|
|Abstract||Rehabilitation Engng is the application of science and technology to ameliorate the handicaps of individuals with disabilities to reintegrate them into society.The goal is to present classical and new rehabilitation engineering principles applied to compensate or enhance motor, sensory, and cognitive deficits. Focus is on the restoration and treatment of the human sensory and vegetative system.|
|Objective||Provide knowledge on the anatomy and physiology of the human sensory system, related dysfunctions and pathologies, and how rehabilitation engineering can provide sensory restoration and substitution.|
This lecture is independent from Rehabilitation Engineering I. Thus, both lectures can be visited in arbitrary order.
|Content||Introduction, problem definition, overview |
Rehabilitation of visual function
- Anatomy and physiology of the visual sense
- Technical aids (glasses, sensor substitution)
- Retina and cortex implants
Rehabilitation of hearing function
- Anatomy and physiology of the auditory sense
- Hearing aids
- Cochlea Implants
Rehabilitation and use of kinesthetic and tactile function
- Anatomy and physiology of the kinesthetic and tactile sense
- Tactile/haptic displays for motion therapy (incl. electrical stimulation)
- Role of displays in motor learning
Rehabilitation of vestibular function
- Anatomy and physiology of the vestibular sense
- Rehabilitation strategies and devices (e.g. BrainPort)
Rehabilitation of vegetative Functions
- Cardiac Pacemaker
- Phrenic stimulation, artificial breathing aids
- Bladder stimulation, artificial sphincter
Brain stimulation and recording
- Deep brain stimulation for patients with Parkinson, epilepsy, depression
- Brain-Computer Interfaces
An Introduction to Rehabilitation Engineering. R. A. Cooper, H. Ohnabe, D. A. Hobson (Eds.). Taylor & Francis, 2007.
Principles of Neural Science. E. R. Kandel, J. H. Schwartz, T. M Jessell (Eds.). Mc Graw Hill, New York, 2000.
Force and Touch Feedback for Virtual Reality. G. C. Burdea (Ed.). Wiley, New York, 1996 (available on NEBIS).
Human Haptic Perception, Basics and Applications. M. Grunwald (Ed.). Birkhäuser, Basel, 2008.
The Sense of Touch and Its Rendering, Springer Tracts in Advanced Robotics 45, A. Bicchi et al.(Eds). Springer-Verlag Berlin, 2008.
Interaktive und autonome Systeme der Medizintechnik - Funktionswiederherstellung und Organersatz. Herausgeber: J. Werner, Oldenbourg Wissenschaftsverlag 2005.
Neural prostheses - replacing motor function after desease or disability. Eds.: R. Stein, H. Peckham, D. Popovic. New York and Oxford: Oxford University Press.
Advances in Rehabilitation Robotics - Human-Friendly Technologies on Movement Assistance and Restoration for People with Disabilities. Eds: Z.Z. Bien, D. Stefanov (Lecture Notes in Control and Information Science, No. 306). Springer Verlag Berlin 2004.
Intelligent Systems and Technologies in Rehabilitation Engineering. Eds: H.N.L. Teodorescu, L.C. Jain (International Series on Computational Intelligence). CRC Press Boca Raton, 2001.
Selected Journal Articles and Web Links:
Abbas, J., Riener, R. (2001) Using mathematical models and advanced control systems techniques to enhance neuroprosthesis function. Neuromodulation 4, pp. 187-195.
Bach-y-Rita P., Tyler M., and Kaczmarek K (2003). Seeing with the brain. International journal of human-computer-interaction, 15(2):285-295.
Burdea, G., Popescu, V., Hentz, V., and Colbert, K. (2000): Virtual reality-based orthopedic telerehabilitation, IEEE Trans. Rehab. Eng., 8, pp. 430-432
Colombo, G., Jörg, M., Schreier, R., Dietz, V. (2000) Treadmill training of paraplegic patients using a robotic orthosis. Journal of Rehabilitation Research and Development, vol. 37, pp. 693-700.
Hayward, V. (2008): A Brief Taxonomy of Tactile Illusions and
Demonstrations That Can Be Done In a Hardware Store. Brain Research Bulletin, Vol 75, No 6, pp 742-752
Krebs, H.I., Hogan, N., Aisen, M.L., Volpe, B.T. (1998): Robot-aided neurorehabilitation, IEEE Trans. Rehab. Eng., 6, pp. 75-87
Levesque. V. (2005). Blindness, technology and haptics. Technical report, McGill University. Available at: http://www.cim.mcgill.ca/~vleves/docs/VL-CIM-TR-05.08.pdf
Quintern, J. (1998) Application of functional electrical stimulation in paraplegic patients. NeuroRehabilitation 10, pp. 205-250.
Riener, R., Nef, T., Colombo, G. (2005) Robot-aided neurorehabilitation for the upper extremities. Medical & Biological Engineering & Computing 43(1), pp. 2-10.
Riener, R. (1999) Model-based development of neuroprostheses for paraplegic patients. Royal Philosophical Transactions: Biological Sciences 354, pp. 877-894.
The vOICe. http://www.seeingwithsound.com.
VideoTact, ForeThought Development, LLC. http://my.execpc.com/?dwysocki/videotac.html
|Prerequisites / Notice||Target Group: |
Students of higher semesters and PhD students of
- D-MAVT, D-ITET, D-INFK, D-HEST
- Biomedical Engineering, Robotics, Systems and Control
- Medical Faculty, University of Zurich
Students of other departments, faculties, courses are also welcome
This lecture is independent from Rehabilitation Engineering I. Thus, both lectures can be visited in arbitrary order.
|376-1279-00L||Virtual Reality in Medicine |
Does not take place this semester.
|W||3 credits||2V||R. Riener|
|Abstract||Virtual Reality has the potential to support medical training and therapy. This lecture will derive the technical principles of multi-modal (audiovisual, haptic, tactile etc.) input devices, displays and rendering techniques. Examples are presented in the fields of surgical training, intra-operative augmentation, and rehabilitation. The lecture is accompanied by practical courses and excursions.|
|Objective||Provide theoretical and practical knowledge of new principles and applications of multi-modal simulation and interface technologies in medical education, therapy, and rehabilitation.|
|Content||Virtual Reality has the potential to provide descriptive and practical information for medical training and therapy while relieving the patient and/or the physician. Multi-modal interactions between the user and the virtual environment facilitate the generation of high-fidelity sensory impressions, by using not only visual and auditory modalities, but also kinesthetic, tactile, and even olfactory feedback. On the basis of the existing physiological constraints, this lecture will derive the technical requirements and principles of multi-modal input devices, displays, and rendering techniques. Several examples are presented that are currently being developed or already applied for surgical training, intra-operative augmentation, and rehabilitation. The lecture will be accompanied by several practical courses on graphical and haptic display devices as well as excursions to facilities equipped with large-scale VR equipment. |
Students of higher semesters and PhD students of
- D-HEST, D-MAVT, D-ITET, D-INFK, D-PHYS
- Robotics, Systems and Control Master
- Biomedical Engineering/Movement Science and Sport
- Medical Faculty, University of Zurich
Students of other departments, faculties, courses are also welcome!
|Literature||Book: Virtual Reality in Medicine. Riener, Robert; Harders, Matthias; 2012 Springer.|
|Prerequisites / Notice||The course language is English. |
Basic experience in Information Technology and Computer Science will be of advantage
More details will be announced in the lecture.
|376-1504-00L||Physical Human Robot Interaction (pHRI) |
Number of participants limited to 26.
|W||4 credits||2V + 2U||R. Gassert, O. Lambercy|
|Abstract||This course focuses on the emerging, interdisciplinary field of physical human-robot interaction, bringing together themes from robotics, real-time control, human factors, haptics, virtual environments, interaction design and other fields to enable the development of human-oriented robotic systems.|
|Objective||The objective of this course is to give an introduction to the fundamentals of physical human robot interaction, through lectures on the underlying theoretical/mechatronics aspects and application fields, in combination with a hands-on lab tutorial. The course will guide students through the design and evaluation process of such systems.|
By the end of this course, you should understand the critical elements in human-robot interactions - both in terms of engineering and human factors - and use these to evaluate and de- sign safe and efficient assistive and rehabilitative robotic systems. Specifically, you should be able to:
1) identify critical human factors in physical human-robot interaction and use these to derive design requirements;
2) compare and select mechatronic components that optimally fulfill the defined design requirements;
3) derive a model of the device dynamics to guide and optimize the selection and integration of selected components
into a functional system;
4) design control hardware and software and implement and
test human-interactive control strategies on the physical
5) characterize and optimize such systems using both engineering and psychophysical evaluation metrics;
6) investigate and optimize one aspect of the physical setup and convey and defend the gained insights in a technical presentation.
|Content||This course provides an introduction to fundamental aspects of physical human-robot interaction. After an overview of human haptic, visual and auditory sensing, neurophysiology and psychophysics, principles of human-robot interaction systems (kinematics, mechanical transmissions, robot sensors and actuators used in these systems) will be introduced. Throughout the course, students will gain knowledge of interaction control strategies including impedance/admittance and force control, haptic rendering basics and issues in device design for humans such as transparency and stability analysis, safety hardware and procedures. The course is organized into lectures that aim to bring students up to speed with the basics of these systems, readings on classical and current topics in physical human-robot interaction, laboratory sessions and lab visits. |
Students will attend periodic laboratory sessions where they will implement the theoretical aspects learned during the lectures. Here the salient features of haptic device design will be identified and theoretical aspects will be implemented in a haptic system based on the haptic paddle (Link), by creating simple dynamic haptic virtual environments and understanding the performance limitations and causes of instabilities (direct/virtual coupling, friction, damping, time delays, sampling rate, sensor quantization, etc.) during rendering of different mechanical properties.
|Lecture notes||Will be distributed through the document repository before the lectures.|
|Literature||Abbott, J. and Okamura, A. (2005). Effects of position quantization and sampling rate on virtual-wall passivity. Robotics, IEEE Transactions on, 21(5):952 - 964.|
Adams, R. and Hannaford, B. (1999). Stable haptic interaction with virtual environments. Robotics and Automation, IEEE Transactions on, 15(3):465 -474.
Buerger, S. and Hogan, N. (2007). Complementary stability and loop shaping for improved human ndash;robot interaction. Robotics, IEEE Transactions on, 23(2):232 -244.
Burdea, G. and Brooks, F. (1996). Force and touch feedback for virtual reality. John Wiley & Sons New York NY.
Colgate, J. and Brown, J. (1994). Factors affecting the z-width of a haptic display. In Robotics and Automation, 1994. Proceedings., 1994 IEEE International Conference on, pages 3205 -3210 vol.4.
Diolaiti, N., Niemeyer, G., Barbagli, F., and Salisbury, J. (2006). Stability of haptic rendering: Discretization, quantization, time delay, and coulomb effects. Robotics, IEEE Transactions on, 22(2):256 -268.
Gillespie, R. and Cutkosky, M. (1996). Stable user-specific haptic rendering of the virtual wall. In Proceedings of the ASME International Mechanical Engineering Congress and Exhibition, volume 58, pages 397-406.
Hannaford, B. and Ryu, J.-H. (2002). Time-domain passivity control of haptic interfaces. Robotics and Automation, IEEE Transactions on, 18(1):1 -10.
Hashtrudi-Zaad, K. and Salcudean, S. (2001). Analysis of control architectures for teleoperation systems with impedance/admittance master and slave manipulators. The International Journal of Robotics Research, 20(6):419.
Hayward, V. and Astley, O. (1996). Performance measures for haptic interfaces. In ROBOTICS RESEARCH-INTERNATIONAL SYMPOSIUM-, volume 7, pages 195-206. Citeseer.
Hayward, V. and Maclean, K. (2007). Do it yourself haptics: part i. Robotics Automation Magazine, IEEE, 14(4):88 -104.
Leskovsky, P., Harders, M., and Szeekely, G. (2006). Assessing the fidelity of haptically rendered deformable objects. In Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2006 14th Symposium on, pages 19 - 25.
MacLean, K. and Hayward, V. (2008). Do it yourself haptics: Part ii [tutorial]. Robotics Automation Magazine, IEEE, 15(1):104 -119.
Mahvash, M. and Hayward, V. (2003). Passivity-based high-fidelity haptic rendering of contact. In Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on, volume 3, pages 3722 - 3728 vol.3.
Mehling, J., Colgate, J., and Peshkin, M. (2005). Increasing the impedance range of a haptic display by adding electrical damping. In Eurohaptics Conference, 2005 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2005. World Haptics 2005. First Joint, pages 257 - 262.
Okamura, A., Richard, C., and Cutkosky, M. (2002). Feeling is believing: Using a force-feedback joystick to teach dynamic systems. JOURNAL OF ENGINEERING EDUCATION-WASHINGTON-, 91(3):345-350.
O'Malley, M. and Goldfarb, M. (2004). The effect of virtual surface stiffness on the haptic perception of detail. Mechatronics, IEEE/ASME Transactions on, 9(2):448 -454.
Richard, C. and Cutkosky, M. (2000). The effects of real and computer generated friction on human performance in a targeting task. In Proceedings of the ASME Dynamic Systems and Control Division, volume 69, page 2.
Salisbury, K., Conti, F., and Barbagli, F. (2004). Haptic rendering: Introductory concepts. Computer Graphics and Applications, IEEE, 24(2):24-32.
Weir, D., Colgate, J., and Peshkin, M. (2008). Measuring and increasing z-width with active electrical damping. In Haptic interfaces for virtual environment and teleoperator systems, 2008. haptics 2008. symposium on, pages 169 -175.
Yasrebi, N. and Constantinescu, D. (2008). Extending the z-width of a haptic device using acceleration feedback. Haptics: Perception, Devices and Scenarios, pages 157-162.
|Prerequisites / Notice||Notice:|
The registration is limited to 26 students
There are 4 credit points for this lecture.
The lecture will be held in English.
The students are expected to have basic control knowledge from previous classes.