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2010


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An experimental analysis of elliptical adhesive contact

Sümer, B., Onal, C. D., Aksak, B., Sitti, M.

Journal of Applied Physics, 107(11):113512, AIP, 2010 (article)

pi

Project Page [BibTex]

2010


Project Page [BibTex]


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Efficient learning and feature detection in high dimensional regression

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

Neural Computation, 22, pages: 831-886, 2010, clmc (article)

Abstract
We present a novel algorithm for efficient learning and feature selection in high- dimensional regression problems. We arrive at this model through a modification of the standard regression model, enabling us to derive a probabilistic version of the well-known statistical regression technique of backfitting. Using the Expectation- Maximization algorithm, along with variational approximation methods to overcome intractability, we extend our algorithm to include automatic relevance detection of the input features. This Variational Bayesian Least Squares (VBLS) approach retains its simplicity as a linear model, but offers a novel statistically robust â??black- boxâ? approach to generalized linear regression with high-dimensional inputs. It can be easily extended to nonlinear regression and classification problems. In particular, we derive the framework of sparse Bayesian learning, e.g., the Relevance Vector Machine, with VBLS at its core, offering significant computational and robustness advantages for this class of methods. We evaluate our algorithm on synthetic and neurophysiological data sets, as well as on standard regression and classification benchmark data sets, comparing it with other competitive statistical approaches and demonstrating its suitability as a drop-in replacement for other generalized linear regression techniques.

am

link (url) [BibTex]

link (url) [BibTex]


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Nanoscale imaging using deep ultraviolet digital holographic microscopy

Faridian, A., Hopp, D., Pedrini, G., Eigenthaler, U., Hirscher, M., Osten, W.

{Optics Express}, 18(13):14159-14164, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Metal-organic frameworks for hydrogen storage

Hirscher, M., Panella, B., Schmitz, B.

{Microporous and Mesoporous Materials}, 129, pages: 335-339, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Samarium-cobalt 2:17 magnets: analysis of the coercive field of Sm2(CoFeCuZr)17 high-temperature permanent magnets

Goll, D., Stadelmaier, H. H., Kronmüller, H.

{Scripta Materialia}, 63, pages: 243-245, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Low-temperature growth of silicon nanotubes and nanowires on amorphous substrates

Mbenkum, B. N., Schneider, A. S., Schütz, G., Xu, C., Richter, G., van Aken, P. A., Majer, G., Spatz, J. P.

{ACS Nano}, 4(4):1805-1812, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Formation and mobility of protonic charge carriers in methyl sulfonic acid-water mixtures: A model for sulfonic acid based ionomers at low degree of hydration

Telfah, A., Majer, G., Kreuer, K. D., Schuster, M., Maier, J.

{Solid State Ionics}, 181, pages: 461-465, 2010 (article)

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[BibTex]

[BibTex]


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Continuous photobleaching to study the growth modes of focal adhesions

de Beer, A. G. F., Majer, G., Roke, S., Spatz, J. P.

{Journal of Adhesion Science and Technology}, 24, pages: 2323-2334, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Magnetic antivortex-core reversal by circular-rotational spin currents

Kamionka, T., Martens, M., Chou, K. W., Curcic, M., Drews, A., Schütz, G., Tyliszczak, T., Stoll, H., Van Waeyenberge, B., Meier, G.

{Physical Review Letters}, 105, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Extension of Yafet\textquotesingles theory of spin relaxation to ferromagnets

Steiauf, D., Illg, C., Fähnle, M.

{Journal of Magnetism and Magnetic Materials}, 322, pages: L5-L7, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Stochastic Differential Dynamic Programming

Theodorou, E., Tassa, Y., Todorov, E.

In the proceedings of American Control Conference (ACC 2010) , 2010, clmc (article)

Abstract
We present a generalization of the classic Differential Dynamic Programming algorithm. We assume the existence of state- and control-dependent process noise, and proceed to derive the second-order expansion of the cost-to-go. Despite having quartic and cubic terms in the initial expression, we show that these vanish, leaving us with the same quadratic structure as standard DDP.

am

PDF [BibTex]

PDF [BibTex]


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Enhanced wet adhesion and shear of elastomeric micro-fiber arrays with mushroom tip geometry and a photopolymerized p (DMA-co-MEA) tip coating

Glass, P., Chung, H., Washburn, N. R., Sitti, M.

Langmuir, 26(22):17357-17362, American Chemical Society, 2010 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Lateral transport of thermal capillary waves

Smith, T. H. R., Vasilyev, O., Maciolek, A., Schmidt, M.

{Europhysics Letters}, 89(1), 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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The formation and propagation of flux avalanches in tailored MgB2 films

Treiber, S., Albrecht, J.

{New Journal of Physics}, 12, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Direct imaging of current induced magnetic vortex gyration in an asymmetric potential well

Bisig, A., Rhensius, J., Kammerer, M., Curcic, M., Stoll, H., Schütz, G., Van Waeyenberge, B., Chou, K. W., Tyliszczak, T., Heyderman, L. J., Krzyk, S., von Bieren, A., Kläui, M.

{Applied Physics Letters}, 96, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Induced magnetism of carbon atoms at the graphene/Ni(111) interface

Weser, M., Rehder, Y., Horn, K., Sicot, M., Fonin, M., Preobrajenski, A. B., Voloshina, E. N., Goering, E., Dedkov, Y. S.

{Applied Physics Letters}, 96, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Photon counting system for time-resolved experiments in multibunch mode

Puzic, A., Korhonen, T., Kalantari, B., Raabe, J., Quitmann, C., Jüllig, P., Bommer, L., Goll, D., Schütz, G., Wintz, S., Strache, T., Körner, M., Markó, D., Bunce, C., Fassbender, J.

{Synchrotron Radiation News}, 23(2):26-32, 2010 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Coupling of Fe and uncompensated Mn moments in exchange-biased Fe/MnPd

Brück, S., Macke, S., Goering, E., Ji, X., Zhan, Q., Krishnan, K. M.

{Physical Review B}, 81(13), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Remarks about spillover and hydrogen adsorption - Comments on the contributions of A.V. Talyzin and R.T. Yang

Hirscher, M.

{Microporous and Mesoporous Materials}, 135, pages: 209-210, 2010 (article)

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DOI [BibTex]


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Grain boundary ridges and triple lines

Straumal, B. B., Sursaeva, V. G., Baretzky, B.

{Scripta Materialia}, 62(12):924-927, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Expanding micelle nanolithography to the self-assembly of multicomponent core-shell nanoparticles

Mbenkum, B. N., D\’\iaz-Ortiz, A., Gu, L., van Aken, P. A., Schütz, G.

{Journal of the American Chemical Society}, 132(31):10671-10673, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Learning control in robotics – trajectory-based opitimal control techniques

Schaal, S., Atkeson, C. G.

Robotics and Automation Magazine, 17(2):20-29, 2010, clmc (article)

Abstract
In a not too distant future, robots will be a natural part of daily life in human society, providing assistance in many areas ranging from clinical applications, education and care giving, to normal household environments [1]. It is hard to imagine that all possible tasks can be preprogrammed in such robots. Robots need to be able to learn, either by themselves or with the help of human supervision. Additionally, wear and tear on robots in daily use needs to be automatically compensated for, which requires a form of continuous self-calibration, another form of learning. Finally, robots need to react to stochastic and dynamic environments, i.e., they need to learn how to optimally adapt to uncertainty and unforeseen changes. Robot learning is going to be a key ingredient for the future of autonomous robots. While robot learning covers a rather large field, from learning to perceive, to plan, to make decisions, etc., we will focus this review on topics of learning control, in particular, as it is concerned with learning control in simulated or actual physical robots. In general, learning control refers to the process of acquiring a control strategy for a particular control system and a particular task by trial and error. Learning control is usually distinguished from adaptive control [2] in that the learning system can have rather general optimization objectivesâ??not just, e.g., minimal tracking errorâ??and is permitted to fail during the process of learning, while adaptive control emphasizes fast convergence without failure. Thus, learning control resembles the way that humans and animals acquire new movement strategies, while adaptive control is a special case of learning control that fulfills stringent performance constraints, e.g., as needed in life-critical systems like airplanes. Learning control has been an active topic of research for at least three decades. However, given the lack of working robots that actually use learning components, more work needs to be done before robot learning will make it beyond the laboratory environment. This article will survey some ongoing and past activities in robot learning to assess where the field stands and where it is going. We will largely focus on nonwheeled robots and less on topics of state estimation, as typically explored in wheeled robots [3]â??6], and we emphasize learning in continuous state-action spaces rather than discrete state-action spaces [7], [8]. We will illustrate the different topics of robot learning with examples from our own research with anthropomorphic and humanoid robots.

am

link (url) [BibTex]

link (url) [BibTex]


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Learning, planning, and control for quadruped locomotion over challenging terrain

Kalakrishnan, M., Buchli, J., Pastor, P., Mistry, M., Schaal, S.

International Journal of Robotics Research, 30(2):236-258, 2010, clmc (article)

Abstract
We present a control architecture for fast quadruped locomotion over rough terrain. We approach the problem by decomposing it into many sub-systems, in which we apply state-of-the-art learning, planning, optimization, and control techniques to achieve robust, fast locomotion. Unique features of our control strategy include: (1) a system that learns optimal foothold choices from expert demonstration using terrain templates, (2) a body trajectory optimizer based on the Zero- Moment Point (ZMP) stability criterion, and (3) a floating-base inverse dynamics controller that, in conjunction with force control, allows for robust, compliant locomotion over unperceived obstacles. We evaluate the performance of our controller by testing it on the LittleDog quadruped robot, over a wide variety of rough terrains of varying difficulty levels. The terrain that the robot was tested on includes rocks, logs, steps, barriers, and gaps, with obstacle sizes up to the leg length of the robot. We demonstrate the generalization ability of this controller by presenting results from testing performed by an independent external test team on terrain that has never been shown to us.

am

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Teleoperated 3-D force feedback from the nanoscale with an atomic force microscope

Onal, C. D., Sitti, M.

IEEE Transactions on nanotechnology, 9(1):46-54, IEEE, 2010 (article)

pi

[BibTex]

[BibTex]


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Roll and pitch motion analysis of a biologically inspired quadruped water runner robot

Park, H. S., Floyd, S., Sitti, M.

The International Journal of Robotics Research, 29(10):1281-1297, SAGE Publications Sage UK: London, England, 2010 (article)

pi

[BibTex]

[BibTex]


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Microstructured elastomeric surfaces with reversible adhesion and examples of their use in deterministic assembly by transfer printing

Kim, Seok, Wu, Jian, Carlson, Andrew, Jin, Sung Hun, Kovalsky, Anton, Glass, Paul, Liu, Zhuangjian, Ahmed, Numair, Elgan, Steven L, Chen, Weiqiu, others

Proceedings of the National Academy of Sciences, 107(40):17095-17100, National Acad Sciences, 2010 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Tankbot: A palm-size, tank-like climbing robot using soft elastomer adhesive treads

Unver, O., Sitti, M.

The International Journal of Robotics Research, 29(14):1761-1777, SAGE Publications Sage UK: London, England, 2010 (article)

pi

[BibTex]

[BibTex]


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Playful Machines: Tutorial

Der, R., Martius, G.

\urlhttp://robot.informatik.uni-leipzig.de/tutorial?lang=en, 2010 (misc)

al

[BibTex]

[BibTex]


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Hydrogen spillover measurements of unbridged and bridged metal-organic frameworks - revisited

Campesi, R., Cuevas, F., Latroche, M., Hirscher, M.

{Physical Chemistry Chemical Physics}, 12, pages: 10457-10459, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Relating Gilbert damping and ultrafast laser-induced demagnetization

Fähnle, M., Seib, J., Illg, C.

{Physical Review B}, 82, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Ferromagnetic properties of the Mn-doped nanograined ZnO films

Straumal, B. B., Protasova, S. G., Mazilkin, A. A., Myatiev, A. A., Straumal, P. B., Schütz, G., Goering, E., Baretzky, B.

{Journal of Applied Physics}, 108, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Ubiquity of ferromagnetic signals in common diamagnetic oxide crystals

Khalid, M., Setzer, A., Ziese, M., Esquinazi, P., Spemann, D., Pöppl, A., Goering, E.

{Physical Review B}, 81(21), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Calculation of the Gilbert damping matrix at low scattering rates in Gd

Seib, J., Fähnle, M.

{Physical Review B}, 82, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Swift heavy ions for controlled modification of soft magnetic properties of Fe0.85N0.15 thin film

Gupta, R., Gupta, A., Bhatt, R., Rüffer, R., Avasthi, D. K.

{Journal of Physics: Condensed Matter}, 22(22), 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Note: Aligned deposition and modal characterization of micron and submicron poly (methyl methacyrlate) fiber cantilevers

Nain, A. S., Filiz, S., Burak Ozdoganlar, O., Sitti, M., Amon, C.

Review of Scientific Instruments, 81(1):016102, AIP, 2010 (article)

pi

[BibTex]

[BibTex]


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Enhanced adhesion of dopamine methacrylamide elastomers via viscoelasticity tuning

Chung, H., Glass, P., Pothen, J. M., Sitti, M., Washburn, N. R.

Biomacromolecules, 12(2):342-347, American Chemical Society, 2010 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Laterally driven interfaces in the three-dimensional Ising lattice gas

Smith, T. H. R., Vasilyev, O., Maciolek, A., Schmidt, M.

{Physical Review E}, 82(2), 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Samarium-cobalt 2:17 magnets: identifying Smn+1Co5n-1 phases stabilized by Zr

Stadelmaier, H. H., Kronmüller, H., Goll, D.

{Scripta Materialia}, 63, pages: 843-846, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Planar metamaterial analogue of electromagnetically induced transparancy for plasmonic sensing

Liu, N., Weiss, T., Mesch, M., Langguth, L., Eigenthaler, U., Hirscher, M., Sönnichsen, C., Giessen, H.

{Nano Letters}, 10, pages: 1103-1107, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Explaining the paradoxical diversity of ultrafast last-induced demagnetization

Koopmans, B., Malinowski, G., Dalla Longa, F., Steiauf, D., Fähnle, M., Roth, T., Cinchetti, M., Aeschlimann, M.

{Nature Materials}, 9, pages: 259-265, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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A high heat of adsorption for hydrogen in magnesium formate

Schmitz, B., Krkljus, I., Leung, E., Höffken, H. W., Müller, U., Hirscher, M.

{ChemSusChem}, 3, pages: 758-761, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Force induced destabilization of adhesion complexes at defined integrin spacings on nanostructured surfaces

de Beer, A. G. F., Cavalcanti-Adam, E. A., Majer, G., López-Garc\’\ia, M., Kessler, H., Spatz, J. P.

{Physical Review E}, 81, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Anisotropic damping of the magnetization dynamics in Ni, Co, and Fe

Gilmore, K., Stiles, M. D., Seib, J., Steiauf, D., Fähnle, M.

{Physical Review B}, 81, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Influence of [Mo6Br8F6]2- cluster inclusion within the mesoporous solid MIL-101 on hydrogen storage performance

Dybtsev, D., Serre, C., Schmitz, B., Panella, B., Hirscher, M., Latroche, M., Llewellyn, P. L., Cordier, S., Molard, Y., Haouas, M., Taulelle, F., Férey, G.

{Langmuir}, 26(13):11283-11290, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Grain boundary layers in nanocrystalline ferromagnetic zinc oxide

Straumal, B. B., Myatiev, A. A., Straumal, P. B., Mazilkin, A. A., Protasova, S. G., Goering, E., Baretzky, B.

{JETP Letters}, 92(6):396-400, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]

2007


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A Tutorial on Spectral Clustering

von Luxburg, U.

Statistics and Computing, 17(4):395-416, December 2007 (article)

Abstract
In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algebra software, and very often outperforms traditional clustering algorithms such as the k-means algorithm. On the first glance spectral clustering appears slightly mysterious, and it is not obvious to see why it works at all and what it really does. The goal of this tutorial is to give some intuition on those questions. We describe different graph Laplacians and their basic properties, present the most common spectral clustering algorithms, and derive those algorithms from scratch by several different approaches. Advantages and disadvantages of the different spectral clustering algorithms are discussed.

ei

PDF PDF DOI [BibTex]

2007


PDF PDF DOI [BibTex]


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A Tutorial on Kernel Methods for Categorization

Jäkel, F., Schölkopf, B., Wichmann, F.

Journal of Mathematical Psychology, 51(6):343-358, December 2007 (article)

Abstract
The abilities to learn and to categorize are fundamental for cognitive systems, be it animals or machines, and therefore have attracted attention from engineers and psychologists alike. Modern machine learning methods and psychological models of categorization are remarkably similar, partly because these two fields share a common history in artificial neural networks and reinforcement learning. However, machine learning is now an independent and mature field that has moved beyond psychologically or neurally inspired algorithms towards providing foundations for a theory of learning that is rooted in statistics and functional analysis. Much of this research is potentially interesting for psychological theories of learning and categorization but also hardly accessible for psychologists. Here, we provide a tutorial introduction to a popular class of machine learning tools, called kernel methods. These methods are closely related to perceptrons, radial-basis-function neural networks and exemplar theories of catego rization. Recent theoretical advances in machine learning are closely tied to the idea that the similarity of patterns can be encapsulated in a positive definite kernel. Such a positive definite kernel can define a reproducing kernel Hilbert space which allows one to use powerful tools from functional analysis for the analysis of learning algorithms. We give basic explanations of some key concepts—the so-called kernel trick, the representer theorem and regularization—which may open up the possibility that insights from machine learning can feed back into psychology.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Accurate Splice site Prediction Using Support Vector Machines

Sonnenburg, S., Schweikert, G., Philips, P., Behr, J., Rätsch, G.

BMC Bioinformatics, 8(Supplement 10):1-16, December 2007 (article)

Abstract
Background: For splice site recognition, one has to solve two classification problems: discriminating true from decoy splice sites for both acceptor and donor sites. Gene finding systems typically rely on Markov Chains to solve these tasks. Results: In this work we consider Support Vector Machines for splice site recognition. We employ the so-called weighted degree kernel which turns out well suited for this task, as we will illustrate in several experiments where we compare its prediction accuracy with that of recently proposed systems. We apply our method to the genome-wide recognition of splice sites in Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Danio rerio, and Homo sapiens. Our performance estimates indicate that splice sites can be recognized very accurately in these genomes and that our method outperforms many other methods including Markov Chains, GeneSplicer and SpliceMachine. We provide genome-wide predictions of splice sites and a stand-alone prediction tool ready to be used for incorporation in a gene finder. Availability: Data, splits, additional information on the model selection, the whole genome predictions, as well as the stand-alone prediction tool are available for download at http:// www.fml.mpg.de/raetsch/projects/splice.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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A unifying framework for robot control with redundant DOFs

Peters, J., Mistry, M., Udwadia, F., Nakanishi, J., Schaal, S.

Autonomous Robots, 24(1):1-12, October 2007 (article)

Abstract
Recently, Udwadia (Proc. R. Soc. Lond. A 2003:1783–1800, 2003) suggested to derive tracking controllers for mechanical systems with redundant degrees-of-freedom (DOFs) using a generalization of Gauss’ principle of least constraint. This method allows reformulating control problems as a special class of optimal controllers. In this paper, we take this line of reasoning one step further and demonstrate that several well-known and also novel nonlinear robot control laws can be derived from this generic methodology. We show experimental verifications on a Sarcos Master Arm robot for some of the derived controllers. The suggested approach offers a promising unification and simplification of nonlinear control law design for robots obeying rigid body dynamics equations, both with or without external constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]