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2017


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Chapter 8 - Micro- and nanorobots in Newtonian and biological viscoelastic fluids

Palagi, S., (Walker) Schamel, D., Qiu, T., Fischer, P.

In Microbiorobotics, pages: 133 - 162, 8, Micro and Nano Technologies, Second edition, Elsevier, Boston, March 2017 (incollection)

Abstract
Swimming microorganisms are a source of inspiration for small scale robots that are intended to operate in fluidic environments including complex biomedical fluids. Nature has devised swimming strategies that are effective at small scales and at low Reynolds number. These include the rotary corkscrew motion that, for instance, propels a flagellated bacterial cell, as well as the asymmetric beat of appendages that sperm cells or ciliated protozoa use to move through fluids. These mechanisms can overcome the reciprocity that governs the hydrodynamics at small scale. The complex molecular structure of biologically important fluids presents an additional challenge for the effective propulsion of microrobots. In this chapter it is shown how physical and chemical approaches are essential in realizing engineered abiotic micro- and nanorobots that can move in biomedically important environments. Interestingly, we also describe a microswimmer that is effective in biological viscoelastic fluids that does not have a natural analogue.

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link (url) DOI [BibTex]

2017


link (url) DOI [BibTex]


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Elements of Causal Inference - Foundations and Learning Algorithms

Peters, J., Janzing, D., Schölkopf, B.

Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

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PDF [BibTex]

PDF [BibTex]


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Appealing Avatars from 3D Body Scans: Perceptual Effects of Stylization

Fleming, R., Mohler, B. J., Romero, J., Black, M. J., Breidt, M.

In Computer Vision, Imaging and Computer Graphics Theory and Applications: 11th International Joint Conference, VISIGRAPP 2016, Rome, Italy, February 27 – 29, 2016, Revised Selected Papers, pages: 175-196, Springer International Publishing, 2017 (inbook)

Abstract
Using styles derived from existing popular character designs, we present a novel automatic stylization technique for body shape and colour information based on a statistical 3D model of human bodies. We investigate whether such stylized body shapes result in increased perceived appeal with two different experiments: One focuses on body shape alone, the other investigates the additional role of surface colour and lighting. Our results consistently show that the most appealing avatar is a partially stylized one. Importantly, avatars with high stylization or no stylization at all were rated to have the least appeal. The inclusion of colour information and improvements to render quality had no significant effect on the overall perceived appeal of the avatars, and we observe that the body shape primarily drives the change in appeal ratings. For body scans with colour information, we found that a partially stylized avatar was perceived as most appealing.

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publisher site pdf DOI [BibTex]

publisher site pdf DOI [BibTex]


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Robot Learning

Peters, J., Lee, D., Kober, J., Nguyen-Tuong, D., Bagnell, J., Schaal, S.

In Springer Handbook of Robotics, pages: 357-394, 15, 2nd, (Editors: Siciliano, Bruno and Khatib, Oussama), Springer International Publishing, 2017 (inbook)

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Project Page [BibTex]

Project Page [BibTex]


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Learning to Filter Object Detections

Prokudin, S., Kappler, D., Nowozin, S., Gehler, P.

In Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland, September 12–15, 2017, Proceedings, pages: 52-62, Springer International Publishing, Cham, 2017 (inbook)

Abstract
Most object detection systems consist of three stages. First, a set of individual hypotheses for object locations is generated using a proposal generating algorithm. Second, a classifier scores every generated hypothesis independently to obtain a multi-class prediction. Finally, all scored hypotheses are filtered via a non-differentiable and decoupled non-maximum suppression (NMS) post-processing step. In this paper, we propose a filtering network (FNet), a method which replaces NMS with a differentiable neural network that allows joint reasoning and re-scoring of the generated set of hypotheses per image. This formulation enables end-to-end training of the full object detection pipeline. First, we demonstrate that FNet, a feed-forward network architecture, is able to mimic NMS decisions, despite the sequential nature of NMS. We further analyze NMS failures and propose a loss formulation that is better aligned with the mean average precision (mAP) evaluation metric. We evaluate FNet on several standard detection datasets. Results surpass standard NMS on highly occluded settings of a synthetic overlapping MNIST dataset and show competitive behavior on PascalVOC2007 and KITTI detection benchmarks.

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Paper link (url) DOI Project Page [BibTex]

Paper link (url) DOI Project Page [BibTex]


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Policy Gradient Methods

Peters, J., Bagnell, J.

In Encyclopedia of Machine Learning and Data Mining, pages: 982-985, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Unsupervised clustering of EOG as a viable substitute for optical eye-tracking

Flad, N., Fomina, T., Bülthoff, H. H., Chuang, L. L.

In First Workshop on Eye Tracking and Visualization (ETVIS 2015), pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

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DOI [BibTex]

DOI [BibTex]


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Mobile Microrobotics

Sitti, M.

Mobile Microrobotics, The MIT Press, Cambridge, MA, 2017 (book)

Abstract
Progress in micro- and nano-scale science and technology has created a demand for new microsystems for high-impact applications in healthcare, biotechnology, manufacturing, and mobile sensor networks. The new robotics field of microrobotics has emerged to extend our interactions and explorations to sub-millimeter scales. This is the first textbook on micron-scale mobile robotics, introducing the fundamentals of design, analysis, fabrication, and control, and drawing on case studies of existing approaches. The book covers the scaling laws that can be used to determine the dominant forces and effects at the micron scale; models forces acting on microrobots, including surface forces, friction, and viscous drag; and describes such possible microfabrication techniques as photo-lithography, bulk micromachining, and deep reactive ion etching. It presents on-board and remote sensing methods, noting that remote sensors are currently more feasible; studies possible on-board microactuators; discusses self-propulsion methods that use self-generated local gradients and fields or biological cells in liquid environments; and describes remote microrobot actuation methods for use in limited spaces such as inside the human body. It covers possible on-board powering methods, indispensable in future medical and other applications; locomotion methods for robots on surfaces, in liquids, in air, and on fluid-air interfaces; and the challenges of microrobot localization and control, in particular multi-robot control methods for magnetic microrobots. Finally, the book addresses current and future applications, including noninvasive medical diagnosis and treatment, environmental remediation, and scientific tools.

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Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]

Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]


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New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481)

Gretton, A., Hennig, P., Rasmussen, C., Schölkopf, B.

Dagstuhl Reports, 6(11):142-167, 2017 (book)

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DOI [BibTex]

DOI [BibTex]


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Statistical Asymmetries Between Cause and Effect

Janzing, D.

In Time in Physics, pages: 129-139, Tutorials, Schools, and Workshops in the Mathematical Sciences, (Editors: Renner, Renato and Stupar, Sandra), Springer International Publishing, Cham, 2017 (inbook)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Robot Learning

Peters, J., Tedrake, R., Roy, N., Morimoto, J.

In Encyclopedia of Machine Learning and Data Mining, pages: 1106-1109, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Design of a visualization scheme for functional connectivity data of Human Brain

Bramlage, L.

Hochschule Osnabrück - University of Applied Sciences, 2017 (thesis)

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Bramlage_BSc_2017.pdf [BibTex]


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Decentralized Simultaneous Multi-target Exploration using a Connected Network of Multiple Robots

Nestmeyer, T., Robuffo Giordano, P., Bülthoff, H. H., Franchi, A.

In pages: 989-1011, Autonomous Robots, 2017 (incollection)

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[BibTex]

[BibTex]


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Momentum-Centered Control of Contact Interactions

Righetti, L., Herzog, A.

In Geometric and Numerical Foundations of Movements, 117, pages: 339-359, Springer Tracts in Advanced Robotics, Springer, Cham, 2017 (incollection)

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link (url) [BibTex]

link (url) [BibTex]

2009


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Text Clustering with Mixture of von Mises-Fisher Distributions

Sra, S., Banerjee, A., Ghosh, J., Dhillon, I.

In Text mining: classification, clustering, and applications, pages: 121-161, Chapman & Hall/CRC data mining and knowledge discovery series, (Editors: Srivastava, A. N. and Sahami, M.), CRC Press, Boca Raton, FL, USA, June 2009 (inbook)

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Web DOI [BibTex]

2009


Web DOI [BibTex]


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Data Mining for Biologists

Tsuda, K.

In Biological Data Mining in Protein Interaction Networks, pages: 14-27, (Editors: Li, X. and Ng, S.-K.), Medical Information Science Reference, Hershey, PA, USA, May 2009 (inbook)

Abstract
In this tutorial chapter, we review basics about frequent pattern mining algorithms, including itemset mining, association rule mining and graph mining. These algorithms can find frequently appearing substructures in discrete data. They can discover structural motifs, for example, from mutation data, protein structures and chemical compounds. As they have been primarily used for business data, biological applications are not so common yet, but their potential impact would be large. Recent advances in computers including multicore machines and ever increasing memory capacity support the application of such methods to larger datasets. We explain technical aspects of the algorithms, but do not go into details. Current biological applications are summarized and possible future directions are given.

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Web [BibTex]

Web [BibTex]


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Large Margin Methods for Part of Speech Tagging

Altun, Y.

In Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, pages: 141-160, (Editors: Keshet, J. and Bengio, S.), Wiley, Hoboken, NJ, USA, January 2009 (inbook)

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Web [BibTex]

Web [BibTex]


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Covariate shift and local learning by distribution matching

Gretton, A., Smola, A., Huang, J., Schmittfull, M., Borgwardt, K., Schölkopf, B.

In Dataset Shift in Machine Learning, pages: 131-160, (Editors: Quiñonero-Candela, J., Sugiyama, M., Schwaighofer, A. and Lawrence, N. D.), MIT Press, Cambridge, MA, USA, 2009 (inbook)

Abstract
Given sets of observations of training and test data, we consider the problem of re-weighting the training data such that its distribution more closely matches that of the test data. We achieve this goal by matching covariate distributions between training and test sets in a high dimensional feature space (specifically, a reproducing kernel Hilbert space). This approach does not require distribution estimation. Instead, the sample weights are obtained by a simple quadratic programming procedure. We provide a uniform convergence bound on the distance between the reweighted training feature mean and the test feature mean, a transductive bound on the expected loss of an algorithm trained on the reweighted data, and a connection to single class SVMs. While our method is designed to deal with the case of simple covariate shift (in the sense of Chapter ??), we have also found benefits for sample selection bias on the labels. Our correction procedure yields its greatest and most consistent advantages when the learning algorithm returns a classifier/regressor that is simpler" than the data might suggest.

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PDF Web [BibTex]

PDF Web [BibTex]


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Metal-Organic Frameworks

Panella, B., Hirscher, M.

In Encyclopedia of Electrochemical Power Sources, pages: 493-496, Elsevier, Amsterdam [et al.], 2009 (incollection)

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[BibTex]

[BibTex]


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Carbon Materials

Hirscher, M.

In Encyclopedia of Electrochemical Power Sources, pages: 484-487, Elsevier, Amsterdam [et al.], 2009 (incollection)

mms

[BibTex]

[BibTex]

2000


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Advances in Large Margin Classifiers

Smola, A., Bartlett, P., Schölkopf, B., Schuurmans, D.

pages: 422, Neural Information Processing, MIT Press, Cambridge, MA, USA, October 2000 (book)

Abstract
The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification--that is, a scale parameter--rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.

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Web [BibTex]

2000


Web [BibTex]


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An Introduction to Kernel-Based Learning Algorithms

Müller, K., Mika, S., Rätsch, G., Tsuda, K., Schölkopf, B.

In Handbook of Neural Network Signal Processing, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (inbook)

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[BibTex]

[BibTex]


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Biomimetic gaze stabilization

Shibata, T., Schaal, S.

In Robot learning: an Interdisciplinary approach, pages: 31-52, (Editors: Demiris, J.;Birk, A.), World Scientific, 2000, clmc (inbook)

Abstract
Accurate oculomotor control is one of the essential pre-requisites for successful visuomotor coordination. In this paper, we suggest a biologically inspired control system for learning gaze stabilization with a biomimetic robotic oculomotor system. In a stepwise fashion, we develop a control circuit for the vestibulo-ocular reflex (VOR) and the opto-kinetic response (OKR), and add a nonlinear learning network to allow adaptivity. We discuss the parallels and differences of our system with biological oculomotor control and suggest solutions how to deal with nonlinearities and time delays in the control system. In simulation and actual robot studies, we demonstrate that our system can learn gaze stabilization in real time in only a few seconds with high final accuracy.

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link (url) [BibTex]

link (url) [BibTex]


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Age-momentum correlation (AMOC)

Stoll, H.

In Construction and Use of an Intense Positron Source at new Linac Facilities in Germany, FZR-295, pages: 44-49, Wissenschaftlich-Technische Berichte, 2000 (incollection)

mms

[BibTex]

[BibTex]


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MeV Positron Beams

Stoll, H.

In Positron Beams and Their Applications, pages: 237-257, World Scientific, Singapore, 2000 (incollection)

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[BibTex]

[BibTex]


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Critical behaviour of V2H in a defective near-surface skin layer

Trenkler, J., Moss, S. C., Reichert, H., Paniago, R., Gebhardt, U., Carstanjen, H. D., Metzger, T. H., Peisl, J.

In Exploration of Subsurface Phenomena by Particle Scattering, pages: 155-164, International Advanced Studies Institute IASI Press, North East/MD, 2000 (incollection)

mms

[BibTex]

[BibTex]