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2012


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Ferromagnetism of nanostructured zinc oxide films

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

{The Physics of Metals and Metallography}, 113(13):1244-1256, 2012 (article)

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DOI [BibTex]

2012


DOI [BibTex]


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Frequencies and polarization vectors of phonons: Results from force constants which are fitted to experimental data or calculated ab initio

Illg, C., Meyer, B., Fähnle, M.

{Physical Review B}, 86(17), Published by the American Physical Society through the American Institute of Physics, Woodbury, NY, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Grain boundary wetting by a second solid phase in the Zr-Nb alloys

Straumal, B. B., Gornakova, A. S., Kucheev, Y. O., Baretzky, B., Nekrasov, A. N.

{Journal of Materials Engineering and Performance}, 21(5):721-724, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Grain boundary wetting in the NdFeB-based hard magnetic alloys

Straumal, B. B., Kucheev, Y. O., Yatskovskaya, I. L., Mogilnikova, I. V., Schütz, G., Nekrasov, A. N., Baretzky, B.

{Journal of Materials Science}, 47(24):8352-8359, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Layered segmentation and optical flow estimation over time

Sun, D., Sudderth, E., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1768-1775, IEEE, 2012 (inproceedings)

Abstract
Layered models provide a compelling approach for estimating image motion and segmenting moving scenes. Previous methods, however, have failed to capture the structure of complex scenes, provide precise object boundaries, effectively estimate the number of layers in a scene, or robustly determine the depth order of the layers. Furthermore, previous methods have focused on optical flow between pairs of frames rather than longer sequences. We show that image sequences with more frames are needed to resolve ambiguities in depth ordering at occlusion boundaries; temporal layer constancy makes this feasible. Our generative model of image sequences is rich but difficult to optimize with traditional gradient descent methods. We propose a novel discrete approximation of the continuous objective in terms of a sequence of depth-ordered MRFs and extend graph-cut optimization methods with new “moves” that make joint layer segmentation and motion estimation feasible. Our optimizer, which mixes discrete and continuous optimization, automatically determines the number of layers and reasons about their depth ordering. We demonstrate the value of layered models, our optimization strategy, and the use of more than two frames on both the Middlebury optical flow benchmark and the MIT layer segmentation benchmark.

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pdf sup mat poster Project Page Project Page [BibTex]

pdf sup mat poster Project Page Project Page [BibTex]


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Towards Associative Skill Memories

Pastor, P., Kalakrishnan, M., Righetti, L., Schaal, S.

In 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), pages: 309-315, IEEE, Osaka, Japan, November 2012 (inproceedings)

Abstract
Movement primitives as basis of movement planning and control have become a popular topic in recent years. The key idea of movement primitives is that a rather small set of stereotypical movements should suffice to create a large set of complex manipulation skills. An interesting side effect of stereotypical movement is that it also creates stereotypical sensory events, e.g., in terms of kinesthetic variables, haptic variables, or, if processed appropriately, visual variables. Thus, a movement primitive executed towards a particular object in the environment will associate a large number of sensory variables that are typical for this manipulation skill. These association can be used to increase robustness towards perturbations, and they also allow failure detection and switching towards other behaviors. We call such movement primitives augmented with sensory associations Associative Skill Memories (ASM). This paper addresses how ASMs can be acquired by imitation learning and how they can create robust manipulation skill by determining subsequent ASMs online to achieve a particular manipulation goal. Evaluation for grasping and manipulation with a Barrett WAM/Hand illustrate our approach.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Template-based learning of grasp selection

Herzog, A., Pastor, P., Kalakrishnan, M., Righetti, L., Asfour, T., Schaal, S.

In 2012 IEEE International Conference on Robotics and Automation, pages: 2379-2384, IEEE, Saint Paul, USA, 2012 (inproceedings)

Abstract
The ability to grasp unknown objects is an important skill for personal robots, which has been addressed by many present and past research projects, but still remains an open problem. A crucial aspect of grasping is choosing an appropriate grasp configuration, i.e. the 6d pose of the hand relative to the object and its finger configuration. Finding feasible grasp configurations for novel objects, however, is challenging because of the huge variety in shape and size of these objects. Moreover, possible configurations also depend on the specific kinematics of the robotic arm and hand in use. In this paper, we introduce a new grasp selection algorithm able to find object grasp poses based on previously demonstrated grasps. Assuming that objects with similar shapes can be grasped in a similar way, we associate to each demonstrated grasp a grasp template. The template is a local shape descriptor for a possible grasp pose and is constructed using 3d information from depth sensors. For each new object to grasp, the algorithm then finds the best grasp candidate in the library of templates. The grasp selection is also able to improve over time using the information of previous grasp attempts to adapt the ranking of the templates. We tested the algorithm on two different platforms, the Willow Garage PR2 and the Barrett WAM arm which have very different hands. Our results show that the algorithm is able to find good grasp configurations for a large set of objects from a relatively small set of demonstrations, and does indeed improve its performance over time.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Reinforcement Learning with Sequences of Motion Primitives for Robust Manipulation

Stulp, F., Theodorou, E., Schaal, S.

IEEE Transactions on Robotics, 2012 (article)

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[BibTex]

[BibTex]


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Impact and Surface Tension in Water: a Study of Landing Bodies

Shih, B., Laham, L., Lee, K. J., Krasnoff, N., Diller, E., Sitti, M.

Bio-inspired Robotics Final Project, Carnegie Mellon University, 2012 (article)

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[BibTex]

[BibTex]


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Design and rolling locomotion of a magnetically actuated soft capsule endoscope

Yim, S., Sitti, M.

IEEE Transactions on Robotics, 28(1):183-194, IEEE, 2012 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Design and manufacturing of a controllable miniature flapping wing robotic platform

Arabagi, V., Hines, L., Sitti, M.

The International Journal of Robotics Research, 31(6):785-800, SAGE Publications Sage UK: London, England, 2012 (article)

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[BibTex]

[BibTex]


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Chemotactic steering of bacteria propelled microbeads

Kim, D., Liu, A., Diller, E., Sitti, M.

Biomedical microdevices, 14(6):1009-1017, Springer US, 2012 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Probabilistic depth image registration incorporating nonvisual information

Wüthrich, M., Pastor, P., Righetti, L., Billard, A., Schaal, S.

In 2012 IEEE International Conference on Robotics and Automation, pages: 3637-3644, IEEE, Saint Paul, USA, 2012 (inproceedings)

Abstract
In this paper, we derive a probabilistic registration algorithm for object modeling and tracking. In many robotics applications, such as manipulation tasks, nonvisual information about the movement of the object is available, which we will combine with the visual information. Furthermore we do not only consider observations of the object, but we also take space into account which has been observed to not be part of the object. Furthermore we are computing a posterior distribution over the relative alignment and not a point estimate as typically done in for example Iterative Closest Point (ICP). To our knowledge no existing algorithm meets these three conditions and we thus derive a novel registration algorithm in a Bayesian framework. Experimental results suggest that the proposed methods perform favorably in comparison to PCL [1] implementations of feature mapping and ICP, especially if nonvisual information is available.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Hartmagnetische L10-FePt basierte gro\ssflächige Nanomuster mittels Nanoimprint-Lithografie

Bublat, T.

Universität Stuttgart, Stuttgart, 2012 (phdthesis)

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[BibTex]

[BibTex]


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Magnetic proximity effect in YBa2Cu3O7 / La2/3Ca1/3MnO3 and YBa2Cu3O7 / LaMnO3+δsuperlattices

Satapathy, D. K., Uribe-Laverde, M. A., Marozau, I., Malik, V. K., Das, S., Wagner, T., Marcelot, C., Stahn, J., Brück, S., Rühm, A., Macke, S., Tietze, T., Goering, E., Frañó, A., Kim, J., Wu, M., Benckiser, E., Keimer, B., Devishvili, A., Toperverg, B. P., Merz, M., Nagel, P., Schuppler, S., Bernhard, C.

{Physical Review Letters}, 108, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Structural and chemical characterization on the nanoscale

Stierle, A., Carstanjen, H.-D., Hofmann, S.

In Nanoelectronics and Information Technology. Advanced Electronic Materials and Novel Devices, pages: 233-254, Wiley-VCH, Weinheim, 2012 (incollection)

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[BibTex]

[BibTex]


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Noble gases and microporous frameworks; from interaction to application

Soleimani Dorcheh, A., Denysenko, D., Volkmer, D., Donner, W., Hirscher, M.

{Microporous and Mesoporous Materials}, 162, pages: 64-68, Elsevier, Amsterdam, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Note: Unique characterization possibilities in the ultra high vacuum scanning transmission x-ray microscope (UHV-STXM) "MAXYMUS" using a rotatable permanent magnetic field up to 0.22 T

Nolle, D., Weigand, M., Audehm, P., Goering, E., Wiesemann, U., Wolter, C., Nolle, E., Schütz, G.

{Review of Scientific Instruments}, 83(4), 2012 (article)

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DOI [BibTex]


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Rutherford Backscattering

Carstanjen, H. D.

In Nanoelectronics and Information Technology. Advanced Electronic Materials and Novel Devices, pages: 250-252, WILEY-VCH Verlag, Weinheim, Germany, 2012 (incollection)

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[BibTex]

[BibTex]


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Microstructure and superconducting properties of MgB2 films prepared by solid state reaction of multilayer precursors of the elements

Kugler, B., Stahl, C., Treiber, S., Soltan, S., Haug, S., Schütz, G., Albrecht, J.

{Thin Solid Films}, 520, pages: 6985-6988, 2012 (article)

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DOI [BibTex]

DOI [BibTex]


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Consumer Depth Cameras for Computer Vision - Research Topics and Applications

Fossati, A., Gall, J., Grabner, H., Ren, X., Konolige, K.

Advances in Computer Vision and Pattern Recognition, Springer, 2012 (book)

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workshop publisher's site [BibTex]

workshop publisher's site [BibTex]


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Spatial Measures between Human Poses for Classification and Understanding

Soren Hauberg, Kim S. Pedersen

In Articulated Motion and Deformable Objects, 7378, pages: 26-36, LNCS, (Editors: Perales, Francisco J. and Fisher, Robert B. and Moeslund, Thomas B.), Springer Berlin Heidelberg, 2012 (inproceedings)

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Publishers site Project Page [BibTex]

Publishers site Project Page [BibTex]


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A Geometric Take on Metric Learning

Hauberg, S., Freifeld, O., Black, M. J.

In Advances in Neural Information Processing Systems (NIPS) 25, pages: 2033-2041, (Editors: P. Bartlett and F.C.N. Pereira and C.J.C. Burges and L. Bottou and K.Q. Weinberger), MIT Press, 2012 (inproceedings)

Abstract
Multi-metric learning techniques learn local metric tensors in different parts of a feature space. With such an approach, even simple classifiers can be competitive with the state-of-the-art because the distance measure locally adapts to the structure of the data. The learned distance measure is, however, non-metric, which has prevented multi-metric learning from generalizing to tasks such as dimensionality reduction and regression in a principled way. We prove that, with appropriate changes, multi-metric learning corresponds to learning the structure of a Riemannian manifold. We then show that this structure gives us a principled way to perform dimensionality reduction and regression according to the learned metrics. Algorithmically, we provide the first practical algorithm for computing geodesics according to the learned metrics, as well as algorithms for computing exponential and logarithmic maps on the Riemannian manifold. Together, these tools let many Euclidean algorithms take advantage of multi-metric learning. We illustrate the approach on regression and dimensionality reduction tasks that involve predicting measurements of the human body from shape data.

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PDF Youtube Suppl. material Poster Project Page [BibTex]

PDF Youtube Suppl. material Poster Project Page [BibTex]

1991


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Ways to smarter CAD-systems

Ehrlenspiel, K., Schaal, S.

In Proceedings of ICED’91Heurista, pages: 10-16, (Editors: Hubka), Edition, Schriftenreihe WDK 21. Zürich, 1991, clmc (inbook)

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[BibTex]

1991


[BibTex]