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2008


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Preface to the Journal of Micro-Nano Mechatronics

Dario, P., Fukuda, T., Sitti, M.

Journal of Micro-Nano Mechatronics, 4(1-2):1-1, Springer-Verlag, 2008 (article)

pi

[BibTex]

2008


[BibTex]


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A legged anchoring mechanism for capsule endoscopes using micropatterned adhesives

Glass, P., Cheung, E., Sitti, M.

IEEE Transactions on Biomedical Engineering, 55(12):2759-2767, IEEE, 2008 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Structure from Behavior in Autonomous Agents

Martius, G., Fiedler, K., Herrmann, J.

In Proc. IEEE Intl. Conf. Intelligent Robots and Systems (IROS 2008), pages: 858 - 862, 2008 (inproceedings)

al

DOI [BibTex]

DOI [BibTex]


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GdFe-Multilagen zur Vergrö\sserung des magnetischen Vortexkerns

Sackmann, V.

Universität Stuttgart, Stuttgart, 2008 (mastersthesis)

mms

[BibTex]

[BibTex]


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Dissipative Magnetisierungsdynamik: Ein Zugang über die ab-initio Elektronentheorie

Steiauf, D.

Universität Stuttgart, Stuttgart, 2008 (phdthesis)

mms

[BibTex]

[BibTex]


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The hole is important! The quest for ferromagnetism in doped ZnO

Tietze, T., Gacic, M., Schütz, G., Jakob, G., Brück, S., Goering, E.

{BESSY Highlights 2007}, pages: 14-15, 2008 (article)

mms

[BibTex]

[BibTex]


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Limitations of a simple quantum mechanical model: Magnetic dichroism in a relativistic one-electron atom

Rodr\’\iguez, J. C., Kostoglou, C., Singer, R., Seib, J., Fähnle, M.

{Physica Status Solidi (B)}, 245(4):735-739, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Impact of irradiation-induced point defects on electronically and ionically induced magnetic relaxation mechanisms in titano-magnetites

Walz, F., Brabers, V. A. M., Kronmüller, H.

{Physica Status Solidi (A)}, 205(12):2934-2942, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Polarization selective magnetic vortex dynamics and core reversal in rotating magnetic fields

Curcic, M., van Waeyenberge, B., Vansteenkiste, A., Weigand, M., Sackmann, V., Stoll, H., Fähnle, M., Tyliszczak, T., Woltersdorf, G., Back, C. H., Schütz, G.

{Physical Review Letters}, 101, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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X-ray spectroscopic investigations of Zn0.94Co0.06O thin films

Mayer, G., Fonin, M., Voss, S., Rüdiger, U., Goering, E.

{IEEE Transactions on Magnetics}, 44(11):2700-2703, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Experimental realization of graded L10-FePt/Fe composite media with perpendicular magnetization

Goll, D., Breitling, A., Gu, L., van Aken, P. A., Sigle, W.

{Journal of Applied Physics}, 104, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Hard magnetic L10 FePt thin films and nanopatterns

Breitling, A., Goll, D.

{Journal of Magnetism and Magnetic Materials}, 320, pages: 1449-1456, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Ma\ssgeschneiderte Speichermaterialien

Hirscher, M.

In Von Brennstoffzellen bis Leuchtdioden (Energie und Chemie - Ein Bündnis für die Zukunft), pages: 31-33, Deutsche Bunsen-Gesellschaft für Physikalische Chemie e.V., Frankfurt am Main, 2008 (incollection)

mms

[BibTex]

[BibTex]


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Spin-reorientation transition in Co/Pt multilayers on nanospheres

Eimüller, T., Ulbrich, T. C., Amaladass, E., Guhr, I. L., Tyliszczak, T., Albrecht, M.

{Physical Review B}, 77, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Non-destructive compositional analysis of historic organ reed pipes

Manescu, A., Fiori, F., Giuliani, A., Kardjilov, N., Kasztovszky, Z., Rustichelli, F., Straumal, B.

{Journal of Physics: Condensed Matter}, 20, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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An advanced magnetic reflectometer

Brück, S., Bauknecht, S., Ludescher, B., Goering, E., Schütz, G.

{Review of Scientific Instruments}, 79, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Computational model for movement learning under uncertain cost

Theodorou, E., Hoffmann, H., Mistry, M., Schaal, S.

In Abstracts of the Society of Neuroscience Meeting (SFN 2008), Washington, DC 2008, 2008, clmc (inproceedings)

Abstract
Stochastic optimal control is a framework for computing control commands that lead to an optimal behavior under a given cost. Despite the long history of optimal control in engineering, it has been only recently applied to describe human motion. So far, stochastic optimal control has been mainly used in tasks that are already learned, such as reaching to a target. For learning, however, there are only few cases where optimal control has been applied. The main assumptions of stochastic optimal control that restrict its application to tasks after learning are the a priori knowledge of (1) a quadratic cost function (2) a state space model that captures the kinematics and/or dynamics of musculoskeletal system and (3) a measurement equation that models the proprioceptive and/or exteroceptive feedback. Under these assumptions, a sequence of control gains is computed that is optimal with respect to the prespecified cost function. In our work, we relax the assumption of the a priori known cost function and provide a computational framework for modeling tasks that involve learning. Typically, a cost function consists of two parts: one part that models the task constraints, like squared distance to goal at movement endpoint, and one part that integrates over the squared control commands. In learning a task, the first part of this cost function will be adapted. We use an expectation-maximization scheme for learning: the expectation step optimizes the task constraints through gradient descent of a reward function and the maximizing step optimizes the control commands. Our computational model is tested and compared with data given from a behavioral experiment. In this experiment, subjects sit in front of a drawing tablet and look at a screen onto which the drawing-pen's position is projected. Beginning from a start point, their task is to move with the pen through a target point presented on screen. Visual feedback about the pen's position is given only before movement onset. At the end of a movement, subjects get visual feedback only about the cost of this trial. In the mapping of the pen's position onto the screen, we added a bias (unknown to subject) and Gaussian noise. Therefore the cost is a function of this bias. The subjects were asked to reach to the target and minimize this cost over trials. In this behavioral experiment, subjects could learn the bias and thus showed reinforcement learning. With our computational model, we could model the learning process over trials. Particularly, the dependence on parameters of the reward function (Gaussian width) and the modulation of movement variance over time were similar in experiment and model.

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[BibTex]

[BibTex]


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Optimization strategies in human reinforcement learning

Hoffmann, H., Theodorou, E., Schaal, S.

Advances in Computational Motor Control VII, Symposium at the Society for Neuroscience Meeting, Washington DC, 2008, 2008, clmc (article)

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PDF [BibTex]

PDF [BibTex]


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A Bayesian approach to empirical local linearizations for robotics

Ting, J., D’Souza, A., Vijayakumar, S., Schaal, S.

In International Conference on Robotics and Automation (ICRA2008), Pasadena, CA, USA, May 19-23, 2008, 2008, clmc (inproceedings)

Abstract
Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics systems where the the dynamics and kinematics are often not faithfully obtainable, empirical linearization may be preferable. In this case, it is important to only use data for the local linearization that lies within a ``reasonable'' linear regime of the system, which can be defined from the Hessian at the point of the linearization -- a quantity that is not available without an analytical model. We introduce a Bayesian approach to solve statistically what constitutes a ``reasonable'' local regime. We approach this problem in the context local linear regression. In contrast to previous locally linear methods, we avoid cross-validation or complex statistical hypothesis testing techniques to find the appropriate local regime. Instead, we treat the parameters of the local regime probabilistically and use approximate Bayesian inference for their estimation. This approach results in an analytical set of iterative update equations that are easily implemented on real robotics systems for real-time applications. As in other locally weighted regressions, our algorithm also lends itself to complete nonlinear function approximation for learning empirical internal models. We sketch the derivation of our Bayesian method and provide evaluations on synthetic data and actual robot data where the analytical linearization was known.

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link (url) [BibTex]

link (url) [BibTex]


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Do humans plan continuous trajectories in kinematic coordinates?

Hoffmann, H., Schaal, S.

In Abstracts of the Society of Neuroscience Meeting (SFN 2008), Washington, DC 2008, 2008, clmc (inproceedings)

Abstract
The planning and execution of human arm movements is still unresolved. An ongoing controversy is whether we plan a movement in kinematic coordinates and convert these coordinates with an inverse internal model into motor commands (like muscle activation) or whether we combine a few muscle synergies or equilibrium points to move a hand, e.g., between two targets. The first hypothesis implies that a planner produces a desired end-effector position for all time points; the second relies on the dynamics of the muscular-skeletal system for a given control command to produce a continuous end-effector trajectory. To distinguish between these two possibilities, we use a visuomotor adaptation experiment. Subjects moved a pen on a graphics tablet and observed the pen's mapped position onto a screen (subjects quickly adapted to this mapping). The task was to move a cursor between two points in a given time window. In the adaptation test, we manipulated the velocity profile of the cursor feedback such that the shape of the trajectories remained unchanged (for straight paths). If humans would use a kinematic plan and map at each time the desired end-effector position onto control commands, subjects should adapt to the above manipulation. In a similar experiment, Wolpert et al (1995) showed adaptation to changes in the curvature of trajectories. This result, however, cannot rule out a shift of an equilibrium point or an additional synergy activation between start and end point of a movement. In our experiment, subjects did two sessions, one control without and one with velocity-profile manipulation. To skew the velocity profile of the cursor trajectory, we added to the current velocity, v, the function 0.8*v*cos(pi + pi*x), where x is the projection of the cursor position onto the start-goal line divided by the distance start to goal (x=0 at the start point). As result, subjects did not adapt to this manipulation: for all subjects, the true hand motion was not significantly modified in a direction consistent with adaptation, despite that the visually presented motion differed significantly from the control motion. One may still argue that this difference in motion was insufficient to be processed visually. Thus, as a control experiment, we replayed control and modified motions to the subjects and asked which of the two motions appeared 'more natural'. Subjects chose the unperturbed motion as more natural significantly better than chance. In summary, for a visuomotor transformation task, the hypothesis of a planned continuous end-effector trajectory predicts adaptation to a modified velocity profile. The current experiment found no adaptation under such transformation.

am

[BibTex]

[BibTex]


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Design and Numerical Modeling of an On-Board Chemical Release Module for Motion Control of Bacteria-Propelled Swimming Micro-Robots

Behkam, B., Nain, A. S., Amon, C. H., Sitti, M.

In ASME 2008 International Mechanical Engineering Congress and Exposition, pages: 239-244, 2008 (inproceedings)

pi

[BibTex]

[BibTex]


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Dynamic modeling of stick slip motion in an untethered magnetic microrobot

Pawashe, C., Floyd, S., Sitti, M.

Proceedings of Robotics: Science and Systems IV, Zurich, Switzerland, 2008 (article)

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[BibTex]

[BibTex]


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Investigation of Calcium Mechanotransduction by Quasi 3-D Microfiber Mechanical Stimulation of Cells

Ruder, W. C., Pratt, E. D., Sitti, M., LeDuc, P. R., Antaki, J. F.

In ASME 2008 Summer Bioengineering Conference, pages: 1049-1050, 2008 (inproceedings)

pi

[BibTex]

[BibTex]


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Beanbag robotics: Robotic swarms with 1-dof units

Kriesel, D. M., Cheung, E., Sitti, M., Lipson, H.

In International Conference on Ant Colony Optimization and Swarm Intelligence, pages: 267-274, 2008 (inproceedings)

pi

[BibTex]

[BibTex]


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Particle image velocimetry and thrust of flagellar micro propulsion systems

Danis, U., Sitti, M., Pekkan, K.

In APS Division of Fluid Dynamics Meeting Abstracts, 1, 2008 (inproceedings)

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[BibTex]

[BibTex]


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Frequency analysis with coupled nonlinear oscillators

Buchli, J., Righetti, L., Ijspeert, A.

Physica D: Nonlinear Phenomena, 237(13):1705-1718, August 2008 (article)

Abstract
We present a method to obtain the frequency spectrum of a signal with a nonlinear dynamical system. The dynamical system is composed of a pool of adaptive frequency oscillators with negative mean-field coupling. For the frequency analysis, the synchronization and adaptation properties of the component oscillators are exploited. The frequency spectrum of the signal is reflected in the statistics of the intrinsic frequencies of the oscillators. The frequency analysis is completely embedded in the dynamics of the system. Thus, no pre-processing or additional parameters, such as time windows, are needed. Representative results of the numerical integration of the system are presented. It is shown, that the oscillators tune to the correct frequencies for both discrete and continuous spectra. Due to its dynamic nature the system is also capable to track non-stationary spectra. Further, we show that the system can be modeled in a probabilistic manner by means of a nonlinear Fokker–Planck equation. The probabilistic treatment is in good agreement with the numerical results, and provides a useful tool to understand the underlying mechanisms leading to convergence.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A modular bio-inspired architecture for movement generation for the infant-like robot iCub

Degallier, S., Righetti, L., Natale, L., Nori, F., Metta, G., Ijspeert, A.

In 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, pages: 795-800, IEEE, Scottsdale, USA, October 2008 (inproceedings)

Abstract
Movement generation in humans appears to be processed through a three-layered architecture, where each layer corresponds to a different level of abstraction in the representation of the movement. In this article, we will present an architecture reflecting this organization and based on a modular approach to human movement generation. We will show that our architecture is well suited for the online generation and modulation of motor behaviors, but also for switching between motor behaviors. This will be illustrated respectively through an interactive drumming task and through switching between reaching and crawling.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Röntgenzirkulardichroische Untersuchungen XMCD an FePt und Ferrit Nanopartikeln

Nolle, D.

Universität Stuttgart, Stuttgart, 2008 (mastersthesis)

mms

[BibTex]

[BibTex]


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Nanostructured biointerfaces for investigating cellular adhesion and differentiation

Gojak, C.

Universität Heidelberg, Heidelberg, 2008 (mastersthesis)

mms

[BibTex]

[BibTex]


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In situ observation of cracks in gold nano-interconnects on flexible substrates

Olliges, S., Gruber, P. A., Orso, S., Auzelyte, V., Ekinci, Y., Solak, H. H., Spolenak, R.

{Scripta Materialia}, 58(3):175-178, 2008 (article)

mms

[BibTex]

[BibTex]


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Transmission electron microscopy study of the intermixing of Fe-Pt multilayers

Kaiser, T., Sigle, W., Goll, D., Goo, N. H., Srot, V., van Aken, P. A., Detemple, E., Jäger, W.

{Journal of Applied Physics}, 103, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Spin state and orbita moments across the metal-insulator-transition of REBaCo2O5.5 investigated by XMCD

Lafkioti, M., Goering, E., Gold, S., Schütz, G., Barilo, S. N., Shiryaev, S. V., Bychkov, G. L., Lemmens, P., Hinkov, V., Deisenhofer, J., Loidl, A.

{New Journal of Physics}, 10, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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A crucial role for primary cilia in cortical morphogenesis

Willaredt, M. A., Hasenpusch-Theil, K., Gardner, H. A. R., Kitanovic, I., Hirschfeld-Warneken, V. C., Gojak, C. P., Gorgas, K., Bradford, C. L., Spatz, J. P., Wölfl, S., Theil, T., Tucker, K. L.

{The Journal of Neuroscience}, 28(48):12887-12900, 2008 (article)

mms

[BibTex]

[BibTex]


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Exchange coupled composite layers for magnetic recording

Goll, D., Macke, S., Kronmüller, H.

{Physica B}, 403, pages: 338-341, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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XMCD studies on Co and Li doped ZnO magnetic semiconductors

Tietze, T., Gacic, M., Schütz, G., Jakob, G., Brück, S., Goering, E.

{New Journal of Physics}, 10, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Desorption studies of hydrogen in metal-organic frameworks

Panella, B., Hönes, K., Müller, U., Trukhan, N., Schubert, M., Pütter, H., Hirscher, M.

{Angewandte Chemie International Edition}, 47, pages: 2138-2142, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Wetting transition of grain-boundary triple junctions

Straumal, B. B., Kogtenkova, O., Zieba, P.

{Acta Materialia}, 56, pages: 925-933, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Time-resolved X-ray microscopy of spin-torque-induced magnetic vortex gyration

Bolte, M., Meier, G., Krüger, B., Drews, A., Eiselt, R., Bocklage, L., Bohlens, S., Tyliszczak, T., Vansteenkiste, A., Van Waeyenberge, B., Chou, K. W., Puzic, A., Stoll, H.

{Physical Review Letters}, 100, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Study of the intermixing of Fe\textendashPt multilayers by analytical and high-resolution transmission electron microscopy

Sigle, W., Kaiser, T., Goll, D., Goo, N. H., Srot, V., van Aken, P. A., Detemple, E., Jäger, W.

In EMC2008, 14th European Microscopy Congress, Vol. 2: Materials Science, pages: 109-110, Springer, Aachen, Germany, 2008 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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The Gilbert equation revisited: anisotropic and nonlocal damping of magnetization dynamics

Fähnle, M., Steiauf, D., Seib, J.

{Journal of Physics D}, 41, 2008 (article)

mms

DOI [BibTex]

DOI [BibTex]

1995


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A kendama learning robot based on a dynamic optimization theory

Miyamoto, H., Gandolfo, F., Gomi, H., Schaal, S., Koike, Y., Osu, R., Nakano, E., Kawato, M.

In Preceedings of the 4th IEEE International Workshop on Robot and Human Communication (RO-MAN’95), pages: 327-332, Tokyo, July 1995, clmc (inproceedings)

am

[BibTex]

1995


[BibTex]


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Visual tracking for moving multiple objects: an integration of vision and control

Sitti, M, Bozma, I, Denker, A

In Industrial Electronics, 1995. ISIE’95., Proceedings of the IEEE International Symposium on, 2, pages: 535-540, 1995 (inproceedings)

pi

[BibTex]

[BibTex]


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Batting a ball: Dynamics of a rhythmic skill

Sternad, D., Schaal, S., Atkeson, C. G.

In Studies in Perception and Action, pages: 119-122, (Editors: Bardy, B.;Bostma, R.;Guiard, Y.), Erlbaum, Hillsdayle, NJ, 1995, clmc (inbook)

am

[BibTex]

[BibTex]


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Memory-based neural networks for robot learning

Atkeson, C. G., Schaal, S.

Neurocomputing, 9, pages: 1-27, 1995, clmc (article)

Abstract
This paper explores a memory-based approach to robot learning, using memory-based neural networks to learn models of the task to be performed. Steinbuch and Taylor presented neural network designs to explicitly store training data and do nearest neighbor lookup in the early 1960s. In this paper their nearest neighbor network is augmented with a local model network, which fits a local model to a set of nearest neighbors. This network design is equivalent to a statistical approach known as locally weighted regression, in which a local model is formed to answer each query, using a weighted regression in which nearby points (similar experiences) are weighted more than distant points (less relevant experiences). We illustrate this approach by describing how it has been used to enable a robot to learn a difficult juggling task. Keywords: memory-based, robot learning, locally weighted regression, nearest neighbor, local models.

am

link (url) [BibTex]

link (url) [BibTex]