Header logo is


2019


no image
Convolutional neural networks: A magic bullet for gravitational-wave detection?

Gebhard, T., Kilbertus, N., Harry, I., Schölkopf, B.

Physical Review D, 100(6):063015, American Physical Society, September 2019 (article)

ei

link (url) DOI [BibTex]

2019


link (url) DOI [BibTex]


no image
Data scarcity, robustness and extreme multi-label classification

Babbar, R., Schölkopf, B.

Machine Learning, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (article)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl motorized device
Implementation of a 6-DOF Parallel Continuum Manipulator for Delivering Fingertip Tactile Cues

Young, E. M., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 12(3):295-306, June 2019 (article)

Abstract
Existing fingertip haptic devices can deliver different subsets of tactile cues in a compact package, but we have not yet seen a wearable six-degree-of-freedom (6-DOF) display. This paper presents the Fuppeteer (short for Fingertip Puppeteer), a device that is capable of controlling the position and orientation of a flat platform, such that any combination of normal and shear force can be delivered at any location on any human fingertip. We build on our previous work of designing a parallel continuum manipulator for fingertip haptics by presenting a motorized version in which six flexible Nitinol wires are actuated via independent roller mechanisms and proportional-derivative controllers. We evaluate the settling time and end-effector vibrations observed during system responses to step inputs. After creating a six-dimensional lookup table and adjusting simulated inputs using measured Jacobians, we show that the device can make contact with all parts of the fingertip with a mean error of 1.42 mm. Finally, we present results from a human-subject study. A total of 24 users discerned 9 evenly distributed contact locations with an average accuracy of 80.5%. Translational and rotational shear cues were identified reasonably well near the center of the fingertip and more poorly around the edges.

hi

DOI [BibTex]


no image
How Does It Feel to Clap Hands with a Robot?

Fitter, N. T., Kuchenbecker, K. J.

International Journal of Social Robotics, 2019 (article) Accepted

Abstract
Future robots may need lighthearted physical interaction capabilities to connect with people in meaningful ways. To begin exploring how users perceive playful human–robot hand-to-hand interaction, we conducted a study with 20 participants. Each user played simple hand-clapping games with the Rethink Robotics Baxter Research Robot during a 1-h-long session involving 24 randomly ordered conditions that varied in facial reactivity, physical reactivity, arm stiffness, and clapping tempo. Survey data and experiment recordings demonstrate that this interaction is viable: all users successfully completed the experiment and mentioned enjoying at least one game without prompting. Hand-clapping tempo was highly salient to users, and human-like robot errors were more widely accepted than mechanical errors. Furthermore, perceptions of Baxter varied in the following statistically significant ways: facial reactivity increased the robot’s perceived pleasantness and energeticness; physical reactivity decreased pleasantness, energeticness, and dominance; higher arm stiffness increased safety and decreased dominance; and faster tempo increased energeticness and increased dominance. These findings can motivate and guide roboticists who want to design social–physical human–robot interactions.

hi

[BibTex]

[BibTex]


no image
X-ray Optics Fabrication Using Unorthodox Approaches

Sanli, U., Baluktsian, M., Ceylan, H., Sitti, M., Weigand, M., Schütz, G., Keskinbora, K.

Bulletin of the American Physical Society, APS, 2019 (article)

mms pi

[BibTex]

[BibTex]


no image
A 32-channel multi-coil setup optimized for human brain shimming at 9.4T

Aghaeifar, A., Zhou, J., Heule, R., Tabibian, B., Schölkopf, B., Jia, F., Zaitsev, M., Scheffler, K.

Magnetic Resonance in Medicine, 2019, (Early View) (article)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl as20205.f2
Microrobotics and Microorganisms: Biohybrid Autonomous Cellular Robots

Alapan, Y., Yasa, O., Yigit, B., Yasa, I. C., Erkoc, P., Sitti, M.

Annual Review of Control, Robotics, and Autonomous Systems, 2019 (article)

pi

[BibTex]

[BibTex]


no image
Enhancing Human Learning via Spaced Repetition Optimization

Tabibian, B., Upadhyay, U., De, A., Zarezade, A., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the National Academy of Sciences, 2019, PNAS published ahead of print January 22, 2019 (article)

ei

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


Thumb xl screenshot 2019 03 25 at 14.29.22
Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots

Büchler, D., Calandra, R., Peters, J.

2019 (article) Submitted

Abstract
High-speed and high-acceleration movements are inherently hard to control. Applying learning to the control of such motions on anthropomorphic robot arms can improve the accuracy of the control but might damage the system. The inherent exploration of learning approaches can lead to instabilities and the robot reaching joint limits at high speeds. Having hardware that enables safe exploration of high-speed and high-acceleration movements is therefore desirable. To address this issue, we propose to use robots actuated by Pneumatic Artificial Muscles (PAMs). In this paper, we present a four degrees of freedom (DoFs) robot arm that reaches high joint angle accelerations of up to 28000 °/s^2 while avoiding dangerous joint limits thanks to the antagonistic actuation and limits on the air pressure ranges. With this robot arm, we are able to tune control parameters using Bayesian optimization directly on the hardware without additional safety considerations. The achieved tracking performance on a fast trajectory exceeds previous results on comparable PAM-driven robots. We also show that our system can be controlled well on slow trajectories with PID controllers due to careful construction considerations such as minimal bending of cables, lightweight kinematics and minimal contact between PAMs and PAMs with the links. Finally, we propose a novel technique to control the the co-contraction of antagonistic muscle pairs. Experimental results illustrate that choosing the optimal co-contraction level is vital to reach better tracking performance. Through the use of PAM-driven robots and learning, we do a small step towards the future development of robots capable of more human-like motions.

ei

Arxiv Video [BibTex]


Thumb xl c8sm02215a f1 hi res
The near and far of a pair of magnetic capillary disks

Koens, L., Wang, W., Sitti, M., Lauga, E.

Soft Matter, 2019 (article)

pi

[BibTex]

[BibTex]


no image
Inferring causation from time series with perspectives in Earth system sciences

Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E., Glymour, C., Kretschmer, M., Mahecha, M., van Nes, E., Peters, J., Quax, R., Reichstein, M., Scheffer, M. S. B., Spirtes, P., Sugihara, G., Sun, J., Zhang, K., Zscheischler, J.

Nature Communications, 2019 (article) In revision

ei

[BibTex]

[BibTex]


Thumb xl mt 2018 00757w 0007
Graphene oxide synergistically enhances antibiotic efficacy in Vancomycin resistance Staphylococcus aureus

Singh, V., Kumar, V., Kashyap, S., Singh, A. V., Kishore, V., Sitti, M., Saxena, P. S., Srivastava, A.

ACS Applied Bio Materials, ACS Publications, 2019 (article)

pi

[BibTex]

[BibTex]


Thumb xl itxm a 1566425 f0001 c
Review of emerging concepts in nanotoxicology: opportunities and challenges for safer nanomaterial design

Singh, A. V., Laux, P., Luch, A., Sudrik, C., Wiehr, S., Wild, A., Santamauro, G., Bill, J., Sitti, M.

Toxicology Mechanisms and Methods, 2019 (article)

pi

[BibTex]

[BibTex]


Thumb xl adtp201800064 fig 0004 m
Mobile microrobots for active therapeutic delivery

Erkoc, P., Yasa, I. C., Ceylan, H., Yasa, O., Alapan, Y., Sitti, M.

Advanced Therapeutics, Wiley Online Library, 2019 (article)

pi

[BibTex]

[BibTex]


Thumb xl adom201801313 fig 0001 m
Microfluidics Integrated Lithography‐Free Nanophotonic Biosensor for the Detection of Small Molecules

Sreekanth, K. V., Sreejith, S., Alapan, Y., Sitti, M., Lim, C. T., Singh, R.

Advanced Optical Materials, 2019 (article)

pi

[BibTex]

[BibTex]


no image
Electromechanical actuation of dielectric liquid crystal elastomers for soft robotics

Davidson, Z., Shahsavan, H., Guo, Y., Hines, L., Xia, Y., Yang, S., Sitti, M.

Bulletin of the American Physical Society, APS, 2019 (article)

pi

[BibTex]

[BibTex]

2001


no image
Regularized principal manifolds

Smola, A., Mika, S., Schölkopf, B., Williamson, R.

Journal of Machine Learning Research, 1, pages: 179-209, June 2001 (article)

Abstract
Many settings of unsupervised learning can be viewed as quantization problems - the minimization of the expected quantization error subject to some restrictions. This allows the use of tools such as regularization from the theory of (supervised) risk minimization for unsupervised learning. This setting turns out to be closely related to principal curves, the generative topographic map, and robust coding. We explore this connection in two ways: (1) we propose an algorithm for finding principal manifolds that can be regularized in a variety of ways; and (2) we derive uniform convergence bounds and hence bounds on the learning rates of the algorithm. In particular, we give bounds on the covering numbers which allows us to obtain nearly optimal learning rates for certain types of regularization operators. Experimental results demonstrate the feasibility of the approach.

ei

PDF [BibTex]

2001


PDF [BibTex]


no image
The psychometric function: II. Bootstrap-based confidence intervals and sampling

Wichmann, F., Hill, N.

Perception and Psychophysics, 63 (8), pages: 1314-1329, 2001 (article)

ei

PDF [BibTex]

PDF [BibTex]


no image
The psychometric function: I. Fitting, sampling and goodness-of-fit

Wichmann, F., Hill, N.

Perception and Psychophysics, 63 (8), pages: 1293-1313, 2001 (article)

Abstract
The psychometric function relates an observer'sperformance to an independent variable, usually some physical quantity of a stimulus in a psychophysical task. This paper, together with its companion paper (Wichmann & Hill, 2001), describes an integrated approach to (1) fitting psychometric functions, (2) assessing the goodness of fit, and (3) providing confidence intervals for the function'sparameters and other estimates derived from them, for the purposes of hypothesis testing. The present paper deals with the first two topics, describing a constrained maximum-likelihood method of parameter estimation and developing several goodness-of-fit tests. Using Monte Carlo simulations, we deal with two specific difficulties that arise when fitting functions to psychophysical data. First, we note that human observers are prone to stimulus-independent errors (or lapses ). We show that failure to account for this can lead to serious biases in estimates of the psychometric function'sparameters and illustrate how the problem may be overcome. Second, we note that psychophysical data sets are usually rather small by the standards required by most of the commonly applied statistical tests. We demonstrate the potential errors of applying traditional X^2 methods to psychophysical data and advocate use of Monte Carlo resampling techniques that do not rely on asymptotic theory. We have made available the software to implement our methods

ei

PDF [BibTex]

PDF [BibTex]


no image
Markovian domain fingerprinting: statistical segmentation of protein sequences

Bejerano, G., Seldin, Y., Margalit, H., Tishby, N.

Bioinformatics, 17(10):927-934, 2001 (article)

ei

PDF Web [BibTex]

PDF Web [BibTex]


no image
Wing transmission for a micromechanical flying insect

Yan, J., Avadhanula, S., Birch, J., Dickinson, M., Sitti, M., Su, T., Fearing, R.

Journal of Micromechatronics, 1(3):221-237, Brill, 2001 (article)

pi

[BibTex]

[BibTex]