Header logo is


2016


no image
Anticipative Interaction Primitives for Human-Robot Collaboration

Maeda, G., Maloo, A., Ewerton, M., Lioutikov, R., Peters, J.

AAAI Fall Symposium Series. Shared Autonomy in Research and Practice, pages: 325-330, November 2016 (conference)

ei

link (url) [BibTex]

2016


link (url) [BibTex]


no image
Unifying distillation and privileged information

Lopez-Paz, D., Schölkopf, B., Bottou, L., Vapnik, V.

International Conference on Learning Representations (ICLR), November 2016 (conference)

ei

Arxiv Project Page [BibTex]

Arxiv Project Page [BibTex]


Thumb xl toc image
Structured light enables biomimetic swimming and versatile locomotion of photoresponsive soft microrobots

Palagi, S., Mark, A. G., Reigh, S. Y., Melde, K., Qiu, T., Zeng, H., Parmeggiani, C., Martella, D., Sanchez-Castillo, A., Kapernaum, N., Giesselmann, F., Wiersma, D. S., Lauga, E., Fischer, P.

Nature Materials, 15(6):647–653, November 2016, Max Planck press release, Nature News & Views. (article)

Abstract
Microorganisms move in challenging environments by periodic changes in body shape. In contrast, current artificial microrobots cannot actively deform, exhibiting at best passive bending under external fields. Here, by taking advantage of the wireless, scalable and spatiotemporally selective capabilities that light allows, we show that soft microrobots consisting of photoactive liquid-crystal elastomers can be driven by structured monochromatic light to perform sophisticated biomimetic motions. We realize continuum yet selectively addressable artificial microswimmers that generate travelling-wave motions to self-propel without external forces or torques, as well as microrobots capable of versatile locomotion behaviours on demand. Both theoretical predictions and experimental results confirm that multiple gaits, mimicking either symplectic or antiplectic metachrony of ciliate protozoa, can be achieved with single microswimmers. The principle of using structured light can be extended to other applications that require microscale actuation with sophisticated spatiotemporal coordination for advanced microrobotic technologies.

pf

Video - Soft photo Micro-Swimmer DOI [BibTex]

Video - Soft photo Micro-Swimmer DOI [BibTex]


no image
Learning High-Order Filters for Efficient Blind Deconvolution of Document Photographs

Xiao, L., Wang, J., Heidrich, W., Hirsch, M.

Computer Vision - ECCV 2016, Lecture Notes in Computer Science, LNCS 9907, Part III, pages: 734-749, (Editors: Bastian Leibe, Jiri Matas, Nicu Sebe and Max Welling), Springer, October 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


no image
Adaptive Training Strategies for BCIs

Sharma, D., Tanneberg, D., Grosse-Wentrup, M., Peters, J., Rueckert, E.

Cybathlon Symposium, October 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


no image
Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies

Osa, T., Peters, J., Neumann, G.

International Symposium on Experimental Robotics (ISER), 1, pages: 160-172, Springer Proceedings in Advanced Robotics, (Editors: Dana Kulic, Yoshihiko Nakamura, Oussama Khatib and Gentiane Venture), Springer, October 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


no image
Stable Reinforcement Learning with Autoencoders for Tactile and Visual Data

van Hoof, H., Chen, N., Karl, M., van der Smagt, P., Peters, J.

Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pages: 3928-3934, IEEE, October 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
A New Trajectory Generation Framework in Robotic Table Tennis

Koc, O., Maeda, G., Peters, J.

Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pages: 3750-3756, October 2016 (conference)

am ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Probabilistic Decomposition of Sequential Force Interaction Tasks into Movement Primitives

Manschitz, S., Gienger, M., Kober, J., Peters, J.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 3920-3927, IEEE, October 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Multi-task logistic regression in brain-computer interfaces

Fiebig, K., Jayaram, V., Peters, J., Grosse-Wentrup, M.

6th Workshop on Brain-Machine Interface Systems at IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016), pages: 002307-002312, IEEE, October 2016 (conference)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Active Tactile Object Exploration with Gaussian Processes

Yi, Z., Calandra, R., Veiga, F., van Hoof, H., Hermans, T., Zhang, Y., Peters, J.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 4925-4930, IEEE, October 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl toc image
Capture of 2D Microparticle Arrays via a UV-Triggered Thiol-yne “Click” Reaction

Walker (Schamel), D., Singh, D. P., Fischer, P.

Advanced Materials, 28(44):9846-9850, September 2016 (article)

Abstract
Immobilization of colloidal assemblies onto solid supports via a fast UV-triggered click-reaction is achieved. Transient assemblies of microparticles and colloidal materials can be captured and transferred to solid supports. The technique does not require complex reaction conditions, and is compatible with a variety of particle assembly methods.

pf

DOI [BibTex]


no image
On Version Space Compression

Ben-David, S., Urner, R.

Algorithmic Learning Theory - 27th International Conference (ALT), 9925, pages: 50-64, Lecture Notes in Computer Science, (Editors: Ortner, R., Simon, H. U., and Zilles, S.), September 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl toc image
Magnesium plasmonics for UV applications and chiral sensing

Jeong, H. H., Mark, A. G., Fischer, P.

Chem. Comm., 52(82):12179-12182, September 2016 (article)

Abstract
We demonstrate that chiral magnesium nanoparticles show remarkable plasmonic extinction- and chiroptical-effects in the ultraviolet region. The Mg nanohelices possess an enhanced local surface plasmon resonance (LSPR) sensitivity due to the strong dispersion of most substances in the UV region.

pf

DOI [BibTex]

DOI [BibTex]


no image
Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller

Abdolmaleki, A., Lau, N., Reis, L., Peters, J., Neumann, G.

Journal of Intelligent & Robotic Systems, 83(3-4):393-408, (Editors: Luis Almeida, Lino Marques ), September 2016, Special Issue: Autonomous Robot Systems (article)

ei

DOI [BibTex]

DOI [BibTex]


no image
Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities

Kohlschuetter, J., Peters, J., Rueckert, E.

XIV Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON), pages: 668-672, (Editors: Kyriacou, E., Christofides, S., and Pattichis, C. S.), September 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


no image
Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes

Grau-Moya, J, Leibfried, F, Genewein, T, Braun, DA

Machine Learning and Knowledge Discovery in Databases, pages: 475-491, Lecture Notes in Computer Science; 9852, Springer, Cham, Switzerland, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD), September 2016 (conference)

Abstract
Information-theoretic principles for learning and acting have been proposed to solve particular classes of Markov Decision Problems. Mathematically, such approaches are governed by a variational free energy principle and allow solving MDP planning problems with information-processing constraints expressed in terms of a Kullback-Leibler divergence with respect to a reference distribution. Here we consider a generalization of such MDP planners by taking model uncertainty into account. As model uncertainty can also be formalized as an information-processing constraint, we can derive a unified solution from a single generalized variational principle. We provide a generalized value iteration scheme together with a convergence proof. As limit cases, this generalized scheme includes standard value iteration with a known model, Bayesian MDP planning, and robust planning. We demonstrate the benefits of this approach in a grid world simulation.

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl 2016 lightfield depth
Depth Estimation Through a Generative Model of Light Field Synthesis

Sajjadi, M. S. M., Köhler, R., Schölkopf, B., Hirsch, M.

Pattern Recognition - 38th German Conference (GCPR), 9796, pages: 426-438, Lecture Notes in Computer Science, (Editors: Rosenhahn, B. and Andres, B.), Springer International Publishing, September 2016 (conference)

ei

Arxiv Project link (url) DOI [BibTex]

Arxiv Project link (url) DOI [BibTex]


Thumb xl cover nature 1j 00008
Holograms for acoustics

Melde, K., Mark, A. G., Qiu, T., Fischer, P.

Nature, 537, pages: 518-522, September 2016, Max Planck press release, Nature News & Views, Nature Video. (article)

Abstract
Holographic techniques are fundamental to applications such as volumetric displays(1), high-density data storage and optical tweezers that require spatial control of intricate optical(2) or acoustic fields(3,4) within a three-dimensional volume. The basis of holography is spatial storage of the phase and/or amplitude profile of the desired wavefront(5,6) in a manner that allows that wavefront to be reconstructed by interference when the hologram is illuminated with a suitable coherent source. Modern computer-generated holography(7) skips the process of recording a hologram from a physical scene, and instead calculates the required phase profile before rendering it for reconstruction. In ultrasound applications, the phase profile is typically generated by discrete and independently driven ultrasound sources(3,4,8-12); however, these can only be used in small numbers, which limits the complexity or degrees of freedom that can be attained in the wavefront. Here we introduce monolithic acoustic holograms, which can reconstruct diffraction-limited acoustic pressure fields and thus arbitrary ultrasound beams. We use rapid fabrication to craft the holograms and achieve reconstruction degrees of freedom two orders of magnitude higher than commercial phased array sources. The technique is inexpensive, appropriate for both transmission and reflection elements, and scales well to higher information content, larger aperture size and higher power. The complex three-dimensional pressure and phase distributions produced by these acoustic holograms allow us to demonstrate new approaches to controlled ultrasonic manipulation of solids in water, and of liquids and solids in air. We expect that acoustic holograms will enable new capabilities in beam-steering and the contactless transfer of power, improve medical imaging, and drive new applications of ultrasound.

pf

Video - Holograms for Sound DOI Project Page [BibTex]

Video - Holograms for Sound DOI Project Page [BibTex]


Thumb xl toc image
A loop-gap resonator for chirality-sensitive nuclear magneto-electric resonance (NMER)

Garbacz, P., Fischer, P., Kraemer, S.

J. Chem. Phys., 145(10):104201, September 2016 (article)

Abstract
Direct detection of molecular chirality is practically impossible by methods of standard nuclear magnetic resonance (NMR) that is based on interactions involving magnetic-dipole and magnetic-field operators. However, theoretical studies provide a possible direct probe of chirality by exploiting an enantiomer selective additional coupling involving magnetic-dipole, magnetic-field, and electric field operators. This offers a way for direct experimental detection of chirality by nuclear magneto-electric resonance (NMER). This method uses both resonant magnetic and electric radiofrequency (RF) fields. The weakness of the chiral interaction though requires a large electric RF field and a small transverse RF magnetic field over the sample volume, which is a non-trivial constraint. In this study, we present a detailed study of the NMER concept and a possible experimental realization based on a loop-gap resonator. For this original device, the basic principle and numerical studies as well as fabrication and measurements of the frequency dependence of the scattering parameter are reported. By simulating the NMER spin dynamics for our device and taking the F-19 NMER signal of enantiomer-pure 1,1,1-trifluoropropan-2-ol, we predict a chirality induced NMER signal that accounts for 1%-5% of the standard achiral NMR signal. Published by AIP Publishing.

pf

DOI [BibTex]

DOI [BibTex]


no image
Bidirektionale Interaktion zwischen Mensch und Roboter beim Bewegungslernen (BIMROB)

Kollegger, G., Ewerton, M., Peters, J., Wiemeyer, J.

11. Symposium der DVS Sportinformatik, September 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


no image
A Low-cost Sensor Glove with Vibrotactile Feedback and Multiple Finger Joint and Hand Motion Sensing for Human-Robot Interaction

Weber, P., Rueckert, E., Calandra, R., Peters, J., Beckerle, P.

25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pages: 99-104, August 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


no image
Experimental and causal view on information integration in autonomous agents

Geiger, P., Hofmann, K., Schölkopf, B.

Proceedings of the 6th International Workshop on Combinations of Intelligent Methods and Applications (CIMA), pages: 21-28, (Editors: Hatzilygeroudis, I. and Palade, V.), August 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


Thumb xl fig1
Soft continuous microrobots with multiple intrinsic degrees of freedom

Palagi, S., Mark, A. G., Melde, K., Zeng, H., Parmeggiani, C., Martella, D., Wiersma, D. S., Fischer, P.

In 2016 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), pages: 1-5, July 2016 (inproceedings)

Abstract
One of the main challenges in the development of microrobots, i.e. robots at the sub-millimeter scale, is the difficulty of adopting traditional solutions for power, control and, especially, actuation. As a result, most current microrobots are directly manipulated by external fields, and possess only a few passive degrees of freedom (DOFs). We have reported a strategy that enables embodiment, remote powering and control of a large number of DOFs in mobile soft microrobots. These consist of photo-responsive materials, such that the actuation of their soft continuous body can be selectively and dynamically controlled by structured light fields. Here we use finite-element modelling to evaluate the effective number of DOFs that are addressable in our microrobots. We also demonstrate that by this flexible approach different actuation patterns can be obtained, and thus different locomotion performances can be achieved within the very same microrobot. The reported results confirm the versatility of the proposed approach, which allows for easy application-specific optimization and online reconfiguration of the microrobot's behavior. Such versatility will enable advanced applications of robotics and automation at the micro scale.

pf

DOI [BibTex]

DOI [BibTex]


no image
Manifold Gaussian Processes for Regression

Calandra, R., Peters, J., Rasmussen, C. E., Deisenroth, M. P.

International Joint Conference on Neural Networks (IJCNN), pages: 3338-3345, IEEE, July 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl toc image
Active Nanorheology with Plasmonics

Jeong, H. H., Mark, A. G., Lee, T., Alarcon-Correa, M., Eslami, S., Qiu, T., Gibbs, J. G., Fischer, P.

Nano Letters, 16(8):4887-4894, July 2016 (article)

Abstract
Nanoplasmonic systems are valued for their strong optical response and their small size. Most plasmonic sensors and systems to date have been rigid and passive. However, rendering these structures dynamic opens new possibilities for applications. Here we demonstrate that dynamic plasmonic nanoparticles can be used as mechanical sensors to selectively probe the rheological properties of a fluid in situ at the nanoscale and in microscopic volumes. We fabricate chiral magneto-plasmonic nanocolloids that can be actuated by an external magnetic field, which in turn allows for the direct and fast modulation of their distinct optical response. The method is robust and allows nanorheological measurements with a mechanical sensitivity of similar to 0.1 cP, even in strongly absorbing fluids with an optical density of up to OD similar to 3 (similar to 0.1% light transmittance) and in the presence of scatterers (e.g., 50% v/v red blood cells).

pf

DOI [BibTex]

DOI [BibTex]


no image
Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills

Maeda, G., Ewerton, M., Koert, D., Peters, J.

IEEE Robotics and Automation Letters, 1(2):784-791, July 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl marss2016
Wireless actuator based on ultrasonic bubble streaming

Qiu, T., Palagi, S., Mark, A. G., Melde, K., Fischer, P.

In 2016 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), pages: 1-5, July 2016 (inproceedings)

Abstract
Miniaturized actuators are a key element for the manipulation and automation at small scales. Here, we propose a new miniaturized actuator, which consists of an array of micro gas bubbles immersed in a fluid. Under ultrasonic excitation, the oscillation of micro gas bubbles results in acoustic streaming and provides a propulsive force that drives the actuator. The actuator was fabricated by lithography and fluidic streaming was observed under ultrasound excitation. Theoretical modelling and numerical simulations were carried out to show that lowing the surface tension results in a larger amplitude of the bubble oscillation, and thus leads to a higher propulsive force. Experimental results also demonstrate that the propulsive force increases 3.5 times when the surface tension is lowered by adding a surfactant. An actuator with a 4×4 mm 2 surface area provides a driving force of about 0.46 mN, suggesting that it is possible to be used as a wireless actuator for small-scale robots and medical instruments.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
The Mondrian Kernel

Balog, M., Lakshminarayanan, B., Ghahramani, Z., Roy, D. M., Teh, Y. W.

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence (UAI), (Editors: Ihler, Alexander T. and Janzing, Dominik), June 2016 (conference)

ei

Arxiv link (url) Project Page [BibTex]

Arxiv link (url) Project Page [BibTex]


no image
Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data

Weichwald, S., Gretton, A., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 6th International Workshop on Pattern Recognition in NeuroImaging (PRNI 2016), June 2016 (conference)

ei

PDF Arxiv Code DOI Project Page [BibTex]

PDF Arxiv Code DOI Project Page [BibTex]


no image
Domain Adaptation with Conditional Transferable Components

Gong, M., Zhang, K., Liu, T., Tao, D., Glymour, C., Schölkopf, B.

Proceedings of the 33nd International Conference on Machine Learning (ICML), 48, pages: 2839-2848, JMLR Workshop and Conference Proceedings, (Editors: Balcan, M.-F. and Weinberger, K. Q.), June 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


no image
Learning Causal Interaction Network of Multivariate Hawkes Processes

Etesami, S., Kiyavash, N., Zhang, K., Singhal, K.

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), June 2016, poster presentation (conference)

ei

[BibTex]

[BibTex]


no image
Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

Wieschollek, P., Wang, O., Sorkine-Hornung, A., Lensch, H. P. A.

29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages: 2027 - 2035, IEEE, June 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


no image
On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection

Zhang, K., Zhang, J., Huang, B., Schölkopf, B., Glymour, C.

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 825-834, (Editors: Ihler, A. and Janzing, D.), AUAI Press, June 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


Thumb xl screen shot 2018 10 09 at 11.42.49
Active Uncertainty Calibration in Bayesian ODE Solvers

Kersting, H., Hennig, P.

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 309-318, (Editors: Ihler, A. and Janzing, D.), AUAI Press, June 2016 (conference)

Abstract
There is resurging interest, in statistics and machine learning, in solvers for ordinary differential equations (ODEs) that return probability measures instead of point estimates. Recently, Conrad et al.~introduced a sampling-based class of methods that are `well-calibrated' in a specific sense. But the computational cost of these methods is significantly above that of classic methods. On the other hand, Schober et al.~pointed out a precise connection between classic Runge-Kutta ODE solvers and Gaussian filters, which gives only a rough probabilistic calibration, but at negligible cost overhead. By formulating the solution of ODEs as approximate inference in linear Gaussian SDEs, we investigate a range of probabilistic ODE solvers, that bridge the trade-off between computational cost and probabilistic calibration, and identify the inaccurate gradient measurement as the crucial source of uncertainty. We propose the novel filtering-based method Bayesian Quadrature filtering (BQF) which uses Bayesian quadrature to actively learn the imprecision in the gradient measurement by collecting multiple gradient evaluations.

ei pn

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


no image
The Arrow of Time in Multivariate Time Serie

Bauer, S., Schölkopf, B., Peters, J.

Proceedings of the 33rd International Conference on Machine Learning (ICML), 48, pages: 2043-2051, JMLR Workshop and Conference Proceedings, (Editors: Balcan, M. F. and Weinberger, K. Q.), JMLR, June 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


no image
A Kernel Test for Three-Variable Interactions with Random Processes

Rubenstein, P. K., Chwialkowski, K. P., Gretton, A.

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence (UAI), (Editors: Ihler, Alexander T. and Janzing, Dominik), June 2016 (conference)

ei

PDF Supplement Arxiv [BibTex]

PDF Supplement Arxiv [BibTex]


no image
Continuous Deep Q-Learning with Model-based Acceleration

Gu, S., Lillicrap, T., Sutskever, I., Levine, S.

Proceedings of the 33nd International Conference on Machine Learning (ICML), 48, pages: 2829-2838, JMLR Workshop and Conference Proceedings, (Editors: Maria-Florina Balcan and Kilian Q. Weinberger), JMLR.org, June 2016 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


no image
Bounded Rational Decision-Making in Feedforward Neural Networks

Leibfried, F, Braun, D

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 407-416, June 2016 (conference)

Abstract
Bounded rational decision-makers transform sensory input into motor output under limited computational resources. Mathematically, such decision-makers can be modeled as information-theoretic channels with limited transmission rate. Here, we apply this formalism for the first time to multilayer feedforward neural networks. We derive synaptic weight update rules for two scenarios, where either each neuron is considered as a bounded rational decision-maker or the network as a whole. In the update rules, bounded rationality translates into information-theoretically motivated types of regularization in weight space. In experiments on the MNIST benchmark classification task for handwritten digits, we show that such information-theoretic regularization successfully prevents overfitting across different architectures and attains results that are competitive with other recent techniques like dropout, dropconnect and Bayes by backprop, for both ordinary and convolutional neural networks.

ei

[BibTex]

[BibTex]


no image
Batch Bayesian Optimization via Local Penalization

González, J., Dai, Z., Hennig, P., Lawrence, N.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 648-657, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C.), May 2016 (conference)

ei pn

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


no image
MuProp: Unbiased Backpropagation for Stochastic Neural Networks

Gu, S., Levine, S., Sutskever, I., Mnih, A.

4th International Conference on Learning Representations (ICLR), May 2016 (conference)

ei

Arxiv [BibTex]

Arxiv [BibTex]


no image
An Improved Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis

Hohmann, M. R., Fomina, T., Jayaram, V., Förster, C., Just, J., M., S., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

Proceedings of the Sixth International BCI Meeting, pages: 44, (Editors: Müller-Putz, G. R. and Huggins, J. E. and Steyrl, D.), BCI, May 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl toc imag
Auxetic Metamaterial Simplifies Soft Robot Design

Mark, A. G., Palagi, S., Qiu, T., Fischer, P.

In 2016 IEEE Int. Conf. on Robotics and Automation (ICRA), pages: 4951-4956, May 2016 (inproceedings)

Abstract
Soft materials are being adopted in robotics in order to facilitate biomedical applications and in order to achieve simpler and more capable robots. One route to simplification is to design the robot's body using `smart materials' that carry the burden of control and actuation. Metamaterials enable just such rational design of the material properties. Here we present a soft robot that exploits mechanical metamaterials for the intrinsic synchronization of two passive clutches which contact its travel surface. Doing so allows it to move through an enclosed passage with an inchworm motion propelled by a single actuator. Our soft robot consists of two 3D-printed metamaterials that implement auxetic and normal elastic properties. The design, fabrication and characterization of the metamaterials are described. In addition, a working soft robot is presented. Since the synchronization mechanism is a feature of the robot's material body, we believe that the proposed design will enable compliant and robust implementations that scale well with miniaturization.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Autofocusing-based correction of B0 fluctuation-induced ghosting

Loktyushin, A., Ehses, P., Schölkopf, B., Scheffler, K.

24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2016 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


no image
Movement Primitives with Multiple Phase Parameters

Ewerton, M., Maeda, G., Neumann, G., Kisner, V., Kollegger, G., Wiemeyer, J., Peters, J.

IEEE International Conference on Robotics and Automation (ICRA), pages: 201-206, IEEE, May 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification

Babbar, R., Muandet, K., Schölkopf, B.

Proceedings of the 2016 SIAM International Conference on Data Mining (SDM), pages: 234-242, (Editors: Sanjay Chawla Venkatasubramanian and Wagner Meira), May 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl 2pamcompressed
A Lightweight Robotic Arm with Pneumatic Muscles for Robot Learning

Büchler, D., Ott, H., Peters, J.

Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 4086-4092, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (conference)

am ei

ICRA16final DOI Project Page [BibTex]

ICRA16final DOI Project Page [BibTex]


Thumb xl untitled
Probabilistic Approximate Least-Squares

Bartels, S., Hennig, P.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 676-684, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C. ), May 2016 (conference)

Abstract
Least-squares and kernel-ridge / Gaussian process regression are among the foundational algorithms of statistics and machine learning. Famously, the worst-case cost of exact nonparametric regression grows cubically with the data-set size; but a growing number of approximations have been developed that estimate good solutions at lower cost. These algorithms typically return point estimators, without measures of uncertainty. Leveraging recent results casting elementary linear algebra operations as probabilistic inference, we propose a new approximate method for nonparametric least-squares that affords a probabilistic uncertainty estimate over the error between the approximate and exact least-squares solution (this is not the same as the posterior variance of the associated Gaussian process regressor). This allows estimating the error of the least-squares solution on a subset of the data relative to the full-data solution. The uncertainty can be used to control the computational effort invested in the approximation. Our algorithm has linear cost in the data-set size, and a simple formal form, so that it can be implemented with a few lines of code in programming languages with linear algebra functionality.

ei pn

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]