Search result: Catalogue data in Autumn Semester 2016
|Mechanical Engineering Master|
|Robotics, Systems and Control|
|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.
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