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459 results (View BibTeX file of all listed publications)

2018

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Wrinkling Instability and Adhesion of a Highly Bendable Gallium Oxide Nanofilm Encapsulating a Liquid-Gallium Droplet

Yunusa, M., Amador, G. J., Drotlef, D., Sitti, M.

Nano Letters, 18(4):2498-2504, March 2018 (article)

Abstract
The wrinkling and interfacial adhesion mechanics of a gallium-oxide nanofilm encapsulating a liquid-gallium droplet are presented. The native oxide nanofilm provides mechanical stability by preventing the flow of the liquid metal. We show how a crumpled oxide skin a few nanometers thick behaves akin to a highly bendable elastic nanofilm under ambient conditions. Upon compression, a wrinkling instability emerges at the contact interface to relieve the applied stress. As the load is further increased, radial wrinkles evolve, and, eventually, the oxide nanofilm ruptures. The observed wrinkling closely resembles the instability experienced by nanofilms under axisymmetric loading, thus providing further insights into the behaviors of elastic nanofilms. Moreover, the mechanical attributes of the oxide skin enable high surface conformation by exhibiting liquid-like behavior. We measured an adhesion energy of 0.238 ± 0.008 J m–2 between a liquid-gallium droplet and smooth flat glass, which is close to the measurements of thin-sheet nanomaterials such as graphene on silicon dioxide.

pi

link (url) DOI [BibTex]

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Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Ornek, E. P., Araujo, H., Yanik, M. F., Sitti, M.

ArXiv e-prints, March 2018 (article)

Abstract
Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a fully dense, non-rigidly deformable, strictly real-time, intraoperative map fusion approach for actively controlled endoscopic capsule robot applications which combines magnetic and vision-based localization, with non-rigid deformations based frame-to-model map fusion. The performance of the proposed method is demonstrated using four different ex-vivo porcine stomach models. Across different trajectories of varying speed and complexity, and four different endoscopic cameras, the root mean square surface reconstruction errors 1.58 to 2.17 cm.

pi

link (url) [BibTex]

pi Turan, M., Almalioglu, Y., Ornek, E. P., Araujo, H., Yanik, M. F., Sitti, M. Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots ArXiv e-prints, March 2018 (article)

link (url) [BibTex]

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Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots

Turan, M., Ornek, E. P., Ibrahimli, N., Giracoglu, C., Almalioglu, Y., Yanik, M. F., Sitti, M.

ArXiv e-prints, March 2018 (article)

Abstract
In the last decade, many medical companies and research groups have tried to convert passive capsule endoscopes as an emerging and minimally invasive diagnostic technology into actively steerable endoscopic capsule robots which will provide more intuitive disease detection, targeted drug delivery and biopsy-like operations in the gastrointestinal(GI) tract. In this study, we introduce a fully unsupervised, real-time odometry and depth learner for monocular endoscopic capsule robots. We establish the supervision by warping view sequences and assigning the re-projection minimization to the loss function, which we adopt in multi-view pose estimation and single-view depth estimation network. Detailed quantitative and qualitative analyses of the proposed framework performed on non-rigidly deformable ex-vivo porcine stomach datasets proves the effectiveness of the method in terms of motion estimation and depth recovery.

pi

link (url) [BibTex]

pi Turan, M., Ornek, E. P., Ibrahimli, N., Giracoglu, C., Almalioglu, Y., Yanik, M. F., Sitti, M. Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots ArXiv e-prints, March 2018 (article)

link (url) [BibTex]

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Self‐Folded Hydrogel Tubes for Implantable Muscular Tissue Scaffolds

Vannozzi, L., Yasa, I. C., Ceylan, H., Menciassi, A., Ricotti, L., Sitti, M.

Macromolecular Bioscience, (0), March 2018 (article)

Abstract
Abstract Programming materials with tunable physical and chemical interactions among its components pave the way of generating 3D functional active microsystems with various potential applications in tissue engineering, drug delivery, and soft robotics. Here, the development of a recapitulated fascicle‐like implantable muscle construct by programmed self‐folding of poly(ethylene glycol) diacrylate hydrogels is reported. The system comprises two stacked layers, each with differential swelling degrees, stiffnesses, and thicknesses in 2D, which folds into a 3D tube together. Inside the tubes, muscle cell adhesion and their spatial alignment are controlled. Both skeletal and cardiac muscle cells also exhibit high viability, and cardiac myocytes preserve their contractile function over the course of 7 d. Integration of biological cells with smart, shape‐changing materials could give rise to the development of new cellular constructs for hierarchical tissue assembly, drug testing platforms, and biohybrid actuators that can perform sophisticated tasks.

pi

link (url) DOI [BibTex]

pi Vannozzi, L., Yasa, I. C., Ceylan, H., Menciassi, A., Ricotti, L., Sitti, M. Self‐Folded Hydrogel Tubes for Implantable Muscular Tissue Scaffolds Macromolecular Bioscience, (0), March 2018 (article)

link (url) DOI [BibTex]

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Redox metals homeostasis in multiple sclerosis and amyotrophic lateral sclerosis: a review

Sheykhansari, S., Kozielski, K., Bill, J., Sitti, M., Gemmati, D., Zamboni, P., Singh, A. V.

Cell Death \& Disease, 9(3):348, March 2018 (article)

Abstract
The effect of redox metals such as iron and copper on multiple sclerosis and amyotrophic lateral sclerosis has been intensively studied. However, the origin of these disorders remains uncertain. This review article critically describes the physiology of redox metals that produce oxidative stress, which in turn leads to cascades of immunomodulatory alteration of neurons in multiple sclerosis and amyotrophic lateral sclerosis. Iron and copper overload has been well established in motor neurons of these diseases' lesions. On the other hand, the role of other metals like cadmium participating indirectly in the redox cascade of neurobiological mechanism is less studied. In the second part of this review, we focus on this less conspicuous correlation between cadmium as an inactive-redox metal and multiple sclerosis and amyotrophic lateral sclerosis, providing novel treatment modalities and approaches as future prospects.

pi

link (url) DOI [BibTex]

pi Sheykhansari, S., Kozielski, K., Bill, J., Sitti, M., Gemmati, D., Zamboni, P., Singh, A. V. Redox metals homeostasis in multiple sclerosis and amyotrophic lateral sclerosis: a review Cell Death \& Disease, 9(3):348, March 2018 (article)

link (url) DOI [BibTex]

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Cancer cells biomineralize ionic gold into nanoparticles-microplates via secreting defense proteins with specific gold-binding peptides

Singh, A. V., Jahnke, T., Kishore, V., Park, B., Batuwangala, M., Bill, J., Sitti, M.

Acta Biomaterialia, March 2018 (article)

Abstract
Cancer cells have the capacity to synthesize nanoparticles (NPs). The detailed mechanism of this process is not very well documented. We report the mechanism of biomineralization of aqueous gold chloride into NPs and microplates in the breast-cancer cell line MCF7. Spherical gold NPs are synthesized in these cells in the presence of serum in the culture media by the reduction of HAuCl4. In the absence of serum, the cells exhibit gold microplate formation through seed-mediate growth albeit slower reduction. The structural characteristics of the two types of NPs under different media conditions were confirmed using scanning electron microscopy (SEM); crystallinity and metallic properties were assessed with transmission electron microscopy (TEM) and x-ray photoelectron spectroscopy (XPS). Gold-reducing proteins, related to cell stress initiate the biomineralization of HAuCl4 in cells (under serum free conditions) as confirmed by infrared (IR) spectroscopy. MCF7 cells undergo irreversible replicative senescence when exposed to a high concentration of ionic gold and conversely remain in a dormant reversible quiescent state when exposed to a low gold concentration. The latter cellular state was achievable in the presence of the rho/ROCK inhibitor Y-27632. Proteomic analysis revealed consistent expression of specific proteins under serum and serum-free conditions. A high-throughput proteomic approach to screen gold-reducing proteins and peptide sequences was utilized and validated by quartz crystal microbalance with dissipation (QCM-D). Statement of significance Cancer cells are known to synthesize gold nanoparticles and microstructures, which are promising for bioimaging and other therapeutic applications. However, the detailed mechanism of such biomineralization process is not well understood yet. Herein, we demonstrate that cancer cells exposed to gold ions (grown in serum/serum-free conditions) secrete shock and stress-related proteins with specific gold-binding/reducing polypeptides. Cells undergo reversible senescence and can recover normal physiology when treated with the senescence inhibitor depending on culture condition. The use of mammalian cells as microincubators for synthesis of such particles could have potential influence on their uptake and biocompatibility. This study has important implications for in-situ reduction of ionic gold to anisotropic micro-nanostructures that could be used in-vivo clinical applications and tumor photothermal therapy.

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link (url) DOI [BibTex]

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An Algorithmic Perspective on Imitation Learning

Osa, T., Pajarinen, J., Neumann, G., Bagnell, J., Abbeel, P., Peters, J.

Foundations and Trends in Robotics, 7(1-2):1-179, March 2018 (article)

ei

DOI Project Page [BibTex]

ei Osa, T., Pajarinen, J., Neumann, G., Bagnell, J., Abbeel, P., Peters, J. An Algorithmic Perspective on Imitation Learning Foundations and Trends in Robotics, 7(1-2):1-179, March 2018 (article)

DOI Project Page [BibTex]

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Assessing body image in anorexia nervosa using biometric self-avatars in virtual reality: Attitudinal components rather than visual body size estimation are distorted

Mölbert, S. C., Thaler, A., Mohler, B. J., Streuber, S., Romero, J., Black, M. J., Zipfel, S., Karnath, H., Giel, K. E.

Psychological Medicine, 48(4):642-653, March 2018 (article)

Abstract
Background: Body image disturbance (BID) is a core symptom of anorexia nervosa (AN), but as yet distinctive features of BID are unknown. The present study aimed at disentangling perceptual and attitudinal components of BID in AN. Methods: We investigated n=24 women with AN and n=24 controls. Based on a 3D body scan, we created realistic virtual 3D bodies (avatars) for each participant that were varied through a range of ±20% of the participants' weights. Avatars were presented in a virtual reality mirror scenario. Using different psychophysical tasks, participants identified and adjusted their actual and their desired body weight. To test for general perceptual biases in estimating body weight, a second experiment investigated perception of weight and shape matched avatars with another identity. Results: Women with AN and controls underestimated their weight, with a trend that women with AN underestimated more. The average desired body of controls had normal weight while the average desired weight of women with AN corresponded to extreme AN (DSM-5). Correlation analyses revealed that desired body weight, but not accuracy of weight estimation, was associated with eating disorder symptoms. In the second experiment, both groups estimated accurately while the most attractive body was similar to Experiment 1. Conclusions: Our results contradict the widespread assumption that patients with AN overestimate their body weight due to visual distortions. Rather, they illustrate that BID might be driven by distorted attitudes with regard to the desired body. Clinical interventions should aim at helping patients with AN to change their desired weight.

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doi pdf DOI Project Page [BibTex]

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Using Probabilistic Movement Primitives in Robotics

Paraschos, A., Daniel, C., Peters, J., Neumann, G.

Autonomous Robots, 42(3):529-551, March 2018 (article)

ei

DOI Project Page [BibTex]

ei Paraschos, A., Daniel, C., Peters, J., Neumann, G. Using Probabilistic Movement Primitives in Robotics Autonomous Robots, 42(3):529-551, March 2018 (article)

DOI Project Page [BibTex]

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A kernel-based approach to learning contact distributions for robot manipulation tasks

Kroemer, O., Leischnig, S., Luettgen, S., Peters, J.

Autonomous Robots, 42(3):581-600, March 2018 (article)

ei

DOI Project Page [BibTex]

ei Kroemer, O., Leischnig, S., Luettgen, S., Peters, J. A kernel-based approach to learning contact distributions for robot manipulation tasks Autonomous Robots, 42(3):581-600, March 2018 (article)

DOI Project Page [BibTex]

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Photogravitactic Microswimmers

Singh, D. P., Uspal, W. E., Popescu, M. N., Wilson, L. G., Fischer, P.

Adv. Func. Mat., 28, pages: 1706660, Febuary 2018 (article)

Abstract
Abstract Phototactic microorganisms are commonly observed to respond to natural sunlight by swimming upward against gravity. This study demonstrates that synthetic photochemically active microswimmers can also swim against gravity. The particles initially sediment and, when illuminated at low light intensities exhibit wall‐bound states of motion near the bottom surface. Upon increasing the intensity of light, the artificial swimmers lift off from the wall and swim against gravity and away from the light source. This motion in the bulk has been further confirmed using holographic microscopy. A theoretical model is presented within the framework of self‐diffusiophoresis, which allows to unequivocally identify the photochemical activity and the phototactic response as key mechanisms in the observed phenomenology. Since the lift‐off threshold intensity depends on the particle size, it can be exploited to selectively address particles with the same density from a polydisperse mixture of active particles and move them in or out of the boundary region. This study provides a simple design strategy to fabricate artificial microswimmers whose two‐ or three‐dimensional swimming behavior can be controlled with light.

pf

link (url) DOI [BibTex]

pf Singh, D. P., Uspal, W. E., Popescu, M. N., Wilson, L. G., Fischer, P. Photogravitactic Microswimmers Adv. Func. Mat., 28, pages: 1706660, Febuary 2018 (article)

link (url) DOI [BibTex]

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Chiral Plasmonic Hydrogen Sensors

Matuschek, M., Singh, D. P., Hyeon-Ho, J., Nesterov, M., Weiss, T., Fischer, P., Neubrech, F., Na Liu, L.

Small, 14(7):1702990, Febuary 2018 (article)

Abstract
In this article, a chiral plasmonic hydrogen‐sensing platform using palladium‐based nanohelices is demonstrated. Such 3D chiral nanostructures fabricated by nanoglancing angle deposition exhibit strong circular dichroism both experimentally and theoretically. The chiroptical properties of the palladium nanohelices are altered upon hydrogen uptake and sensitively depend on the hydrogen concentration. Such properties are well suited for remote and spark‐free hydrogen sensing in the flammable range. Hysteresis is reduced, when an increasing amount of gold is utilized in the palladium‐gold hybrid helices. As a result, the linearity of the circular dichroism in response to hydrogen is significantly improved. The chiral plasmonic sensor scheme is of potential interest for hydrogen‐sensing applications, where good linearity and high sensitivity are required.

pf

link (url) DOI [BibTex]

pf Matuschek, M., Singh, D. P., Hyeon-Ho, J., Nesterov, M., Weiss, T., Fischer, P., Neubrech, F., Na Liu, L. Chiral Plasmonic Hydrogen Sensors Small, 14(7):1702990, Febuary 2018 (article)

link (url) DOI [BibTex]

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Thermocapillary-driven fluid flow within microchannels

Amador, G. J., Tabak, A. F., Ren, Z., Alapan, Y., Yasa, O., Sitti, M.

ArXiv e-prints, Febuary 2018 (article)

Abstract
Surface tension gradients induce Marangoni flow, which may be exploited for fluid transport. At the micrometer scale, these surface-driven flows can be more significant than those driven by pressure. By introducing fluid-fluid interfaces on the walls of microfluidic channels, we use surface tension gradients to drive bulk fluid flows. The gradients are specifically induced through thermal energy, exploiting the temperature dependence of a fluid-fluid interface to generate thermocapillary flow. In this report, we provide the design concept for a biocompatible, thermocapillary microchannel capable of being powered by solar irradiation. Using temperature gradients on the order of degrees Celsius per centimeter, we achieve fluid velocities on the order of millimeters per second. Following experimental observations, fluid dynamic models, and numerical simulation, we find that the fluid velocity is linearly proportional to the provided temperature gradient, enabling full control of the fluid flow within the microchannels.

pi

link (url) Project Page [BibTex]

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Sparse-then-dense alignment-based 3D map reconstruction method for endoscopic capsule robots

Turan, M., Pilavci, Y. Y., Ganiyusufoglu, I., Araujo, H., Konukoglu, E., Sitti, M.

Machine Vision and Applications, 29(2):345-359, Febuary 2018 (article)

Abstract
Despite significant progress achieved in the last decade to convert passive capsule endoscopes to actively controllable robots, robotic capsule endoscopy still has some challenges. In particular, a fully dense three-dimensional (3D) map reconstruction of the explored organ remains an unsolved problem. Such a dense map would help doctors detect the locations and sizes of the diseased areas more reliably, resulting in more accurate diagnoses. In this study, we propose a comprehensive medical 3D reconstruction method for endoscopic capsule robots, which is built in a modular fashion including preprocessing, keyframe selection, sparse-then-dense alignment-based pose estimation, bundle fusion, and shading-based 3D reconstruction. A detailed quantitative analysis is performed using a non-rigid esophagus gastroduodenoscopy simulator, four different endoscopic cameras, a magnetically activated soft capsule robot, a sub-millimeter precise optical motion tracker, and a fine-scale 3D optical scanner, whereas qualitative ex-vivo experiments are performed on a porcine pig stomach. To the best of our knowledge, this study is the first complete endoscopic 3D map reconstruction approach containing all of the necessary functionalities for a therapeutically relevant 3D map reconstruction.

pi

link (url) DOI [BibTex]

pi Turan, M., Pilavci, Y. Y., Ganiyusufoglu, I., Araujo, H., Konukoglu, E., Sitti, M. Sparse-then-dense alignment-based 3D map reconstruction method for endoscopic capsule robots Machine Vision and Applications, 29(2):345-359, Febuary 2018 (article)

link (url) DOI [BibTex]

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Body size estimation of self and others in females varying in BMI

Thaler, A., Geuss, M. N., Mölbert, S. C., Giel, K. E., Streuber, S., Romero, J., Black, M. J., Mohler, B. J.

PLoS ONE, 13(2), Febuary 2018 (article)

Abstract
Previous literature suggests that a disturbed ability to accurately identify own body size may contribute to overweight. Here, we investigated the influence of personal body size, indexed by body mass index (BMI), on body size estimation in a non-clinical population of females varying in BMI. We attempted to disentangle general biases in body size estimates and attitudinal influences by manipulating whether participants believed the body stimuli (personalized avatars with realistic weight variations) represented their own body or that of another person. Our results show that the accuracy of own body size estimation is predicted by personal BMI, such that participants with lower BMI underestimated their body size and participants with higher BMI overestimated their body size. Further, participants with higher BMI were less likely to notice the same percentage of weight gain than participants with lower BMI. Importantly, these results were only apparent when participants were judging a virtual body that was their own identity (Experiment 1), but not when they estimated the size of a body with another identity and the same underlying body shape (Experiment 2a). The different influences of BMI on accuracy of body size estimation and sensitivity to weight change for self and other identity suggests that effects of BMI on visual body size estimation are self-specific and not generalizable to other bodies.

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pdf DOI Project Page [BibTex]

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Independent Actuation of Two-Tailed Microrobots

Khalil, I. S. M., Tabak, A. F., Hamed, Y., Tawakol, M., Klingner, A., Gohary, N. E., Mizaikoff, B., Sitti, M.

IEEE Robotics and Automation Letters, 3(3):1703-1710, Febuary 2018 (article)

Abstract
A soft two-tailed microrobot in low Reynolds number fluids does not achieve forward locomotion by identical tails regardless to its wiggling frequency. If the tails are nonidentical, zero forward locomotion is also observed at specific oscillation frequencies (which we refer to as the reversal frequencies), as the propulsive forces imparted to the fluid by each tail are almost equal in magnitude and opposite in direction. We find distinct reversal frequencies for the two-tailed microrobots based on their tail length ratio. At these frequencies, the microrobot achieves negligible net displacement under the influence of a periodic magnetic field. This observation allows us to fabricate groups of microrobots with tail length ratio of 1.24 ± 0.11, 1.48 ± 0.08, and 1.71 ± 0.09. We demonstrate selective actuation of microrobots based on prior characterization of their reversal frequencies. We also implement simultaneous flagellar propulsion of two microrobots and show that they can be controlled to swim along the same direction and opposite to each other using common periodic magnetic fields. In addition, independent motion control of two microrobots is achieved toward two different reference positions with average steady-state error of 110.1 ± 91.8 μm and 146.9 ± 105.9 μm.

pi

link (url) DOI [BibTex]

pi Khalil, I. S. M., Tabak, A. F., Hamed, Y., Tawakol, M., Klingner, A., Gohary, N. E., Mizaikoff, B., Sitti, M. Independent Actuation of Two-Tailed Microrobots IEEE Robotics and Automation Letters, 3(3):1703-1710, Febuary 2018 (article)

link (url) DOI [BibTex]

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Recent Advances in Wearable Transdermal Delivery Systems

Amjadi, M., Sheykhansari, S., Nelson, B. J., Sitti, M.

Advanced Materials, 30(7):1704530, January 2018 (article)

Abstract
Abstract Wearable transdermal delivery systems have recently received tremendous attention due to their noninvasive, convenient, and prolonged administration of pharmacological agents. Here, the material prospects, fabrication processes, and drug‐release mechanisms of these types of therapeutic delivery systems are critically reviewed. The latest progress in the development of multifunctional wearable devices capable of closed‐loop sensation and drug delivery is also discussed. This survey reveals that wearable transdermal delivery has already made an impact in diverse healthcare applications, while several grand challenges remain.

pi

link (url) DOI [BibTex]

pi Amjadi, M., Sheykhansari, S., Nelson, B. J., Sitti, M. Recent Advances in Wearable Transdermal Delivery Systems Advanced Materials, 30(7):1704530, January 2018 (article)

link (url) DOI [BibTex]

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Acoustic Fabrication via the Assembly and Fusion of Particles

Melde, K., Choi, E., Wu, Z., Palagi, S., Qiu, T., Fischer, P.

Advanced Materials, 30(3):1704507, January 2018 (article)

Abstract
Acoustic assembly promises a route toward rapid parallel fabrication of whole objects directly from solution. This study reports the contact-free and maskless assembly, and fixing of silicone particles into arbitrary 2D shapes using ultrasound fields. Ultrasound passes through an acoustic hologram to form a target image. The particles assemble from a suspension along lines of high pressure in the image due to acoustic radiation forces and are then fixed (crosslinked) in a UV-triggered reaction. For this, the particles are loaded with a photoinitiator by solvent-induced swelling. This localizes the reaction and allows the bulk suspension to be reused. The final fabricated parts are mechanically stable and self-supporting.

pf

link (url) DOI Project Page [BibTex]

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Deep EndoVO: A recurrent convolutional neural network (RCNN) based visual odometry approach for endoscopic capsule robots

Turan, M., Almalioglu, Y., Araujo, H., Konukoglu, E., Sitti, M.

Neurocomputing, 275, pages: 1861 - 1870, January 2018 (article)

Abstract
Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep recurrent convolutional neural networks (RCNNs) for the visual odometry task, where convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories.

pi

link (url) DOI [BibTex]

pi Turan, M., Almalioglu, Y., Araujo, H., Konukoglu, E., Sitti, M. Deep EndoVO: A recurrent convolutional neural network (RCNN) based visual odometry approach for endoscopic capsule robots Neurocomputing, 275, pages: 1861 - 1870, January 2018 (article)

link (url) DOI [BibTex]

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Small-scale soft-bodied robot with multimodal locomotion

Hu, W., Lum, G. Z., Mastrangeli, M., Sitti, M.

Nature, 554, pages: 81-85, Nature, January 2018 (article)

Abstract
Untethered small-scale (from several millimetres down to a few micrometres in all dimensions) robots that can non-invasively access confined, enclosed spaces may enable applications in microfactories such as the construction of tissue scaffolds by robotic assembly1, in bioengineering such as single-cell manipulation and biosensing2, and in healthcare3,4,5,6 such as targeted drug delivery4 and minimally invasive surgery3,5. Existing small-scale robots, however, have very limited mobility because they are unable to negotiate obstacles and changes in texture or material in unstructured environments7,8,9,10,11,12,13. Of these small-scale robots, soft robots have greater potential to realize high mobility via multimodal locomotion, because such machines have higher degrees of freedom than their rigid counterparts14,15,16. Here we demonstrate magneto-elastic soft millimetre-scale robots that can swim inside and on the surface of liquids, climb liquid menisci, roll and walk on solid surfaces, jump over obstacles, and crawl within narrow tunnels. These robots can transit reversibly between different liquid and solid terrains, as well as switch between locomotive modes. They can additionally execute pick-and-place and cargo-release tasks. We also present theoretical models to explain how the robots move. Like the large-scale robots that can be used to study locomotion17, these soft small-scale robots could be used to study soft-bodied locomotion produced by small organisms.

pi

link (url) DOI Project Page [BibTex]

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Light‐Driven Janus Hollow Mesoporous TiO2–Au Microswimmers

Sridhar, V., Park, B., Sitti, M.

Advanced Functional Materials, 28(5):1704902, January 2018 (article)

Abstract
Abstract Light‐driven microswimmers have garnered attention for their potential use in various applications, such as environmental remediation, hydrogen evolution, and targeted drug delivery. Janus hollow mesoporous TiO2/Au (JHP–TiO2–Au) microswimmers with enhanced swimming speeds under low‐intensity ultraviolet (UV) light are presented. The swimmers show enhanced swimming speeds both in presence and absence of H2O2. The microswimmers move due to self‐electrophoresis when UV light is incident on them. There is a threefold increase in speed of JHP–TiO2–Au microswimmers in comparison with Janus solid TiO2/Au (JS–TiO2–Au) microswimmers. This increase in their speed is due to the increase in surface area of the porous swimmers and their hollow structure. These microswimmers are also made steerable by using a thin Co magnetic layer. They can be used in potential environmental applications for active photocatalytic degradation of methylene blue and targeted active drug delivery of an anticancer drug (doxurobicin) in vitro in H2O2 solution. Their increased speed from the presence of a hollow mesoporous structure is beneficial for future potential applications, such as hydrogen evolution, selective heterogeneous photocatalysis, and targeted cargo delivery.

pi

link (url) DOI Project Page [BibTex]

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Mechanical Rubbing of Blood Clots Using Helical Robots Under Ultrasound Guidance

Khalil, I. S. M., Mahdy, D., Sharkawy, A. E., Moustafa, R. R., Tabak, A. F., Mitwally, M. E., Hesham, S., Hamdi, N., Klingner, A., Mohamed, A., Sitti, M.

IEEE Robotics and Automation Letters, 3(2):1112-1119, January 2018 (article)

Abstract
A simple way to mitigate the potential negative sideeffects associated with chemical lysis of a blood clot is to tear its fibrin network via mechanical rubbing using a helical robot. Here, we achieve mechanical rubbing of blood clots under ultrasound guidance and using external magnetic actuation. Position of the helical robot is determined using ultrasound feedback and used to control its motion toward the clot, whereas the volume of the clots is estimated simultaneously using visual feedback. We characterize the shear modulus and ultimate shear strength of the blood clots to predict their removal rate during rubbing. Our in vitro experiments show the ability to move the helical robot controllably toward clots using ultrasound feedback with average and maximum errors of 0.84 ± 0.41 and 2.15 mm, respectively, and achieve removal rate of -0.614 ± 0.303 mm3/min at room temperature (25 °C) and -0.482 ± 0.23 mm3/min at body temperature (37 °C), under the influence of two rotating dipole fields at frequency of 35 Hz. We also validate the effectiveness of mechanical rubbing by measuring the number of red blood cells and platelets past the clot. Our measurements show that rubbing achieves cell count of (46 ± 10.9) × 104 cell/ml, whereas the count in the absence of rubbing is (2 ± 1.41) × 104 cell/ml, after 40 min.

pi

link (url) DOI [BibTex]

pi Khalil, I. S. M., Mahdy, D., Sharkawy, A. E., Moustafa, R. R., Tabak, A. F., Mitwally, M. E., Hesham, S., Hamdi, N., Klingner, A., Mohamed, A., Sitti, M. Mechanical Rubbing of Blood Clots Using Helical Robots Under Ultrasound Guidance IEEE Robotics and Automation Letters, 3(2):1112-1119, January 2018 (article)

link (url) DOI [BibTex]

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Distributed Event-Based State Estimation for Networked Systems: An LMI Approach

Muehlebach, M., Trimpe, S.

IEEE Transactions on Automatic Control, 63(1):269-276, January 2018 (article)

am ics

arXiv (extended version) DOI Project Page [BibTex]

am ics Muehlebach, M., Trimpe, S. Distributed Event-Based State Estimation for Networked Systems: An LMI Approach IEEE Transactions on Automatic Control, 63(1):269-276, January 2018 (article)

arXiv (extended version) DOI Project Page [BibTex]

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Approximate Value Iteration Based on Numerical Quadrature

Vinogradska, J., Bischoff, B., Peters, J.

IEEE Robotics and Automation Letters, 3(2):1330-1337, January 2018 (article)

ei

DOI Project Page [BibTex]

ei Vinogradska, J., Bischoff, B., Peters, J. Approximate Value Iteration Based on Numerical Quadrature IEEE Robotics and Automation Letters, 3(2):1330-1337, January 2018 (article)

DOI Project Page [BibTex]

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Biomimetic Tactile Sensors and Signal Processing with Spike Trains: A Review

Yi, Z., Zhang, Y., Peters, J.

Sensors and Actuators A: Physical, 269, pages: 41-52, January 2018 (article)

ei

DOI Project Page [BibTex]

ei Yi, Z., Zhang, Y., Peters, J. Biomimetic Tactile Sensors and Signal Processing with Spike Trains: A Review Sensors and Actuators A: Physical, 269, pages: 41-52, January 2018 (article)

DOI Project Page [BibTex]

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Measurement of Spectral Functions of Ultracold Atoms in Disordered Potentials

Volchkov, V., Pasek, M., Denechaud, V., Mukhtar, M., Aspect, A., Delande, D., Josse, V.

Physical Review Letters, 120, pages: 060404, American Physical Society (APS), January 2018 (article)

Abstract
We report on the measurement of the spectral functions of noninteracting ultracold atoms in a three-dimensional disordered potential resulting from an optical speckle field. Varying the disorder strength by 2 orders of magnitude, we observe the crossover from the “quantum” perturbative regime of low disorder to the “classical” regime at higher disorder strength, and find an excellent agreement with numerical simulations. The method relies on the use of state-dependent disorder and the controlled transfer of atoms to create well-defined energy states. This opens new avenues for experimental investigations of three-dimensional Anderson localization.

sf

DOI [BibTex]

sf Volchkov, V., Pasek, M., Denechaud, V., Mukhtar, M., Aspect, A., Delande, D., Josse, V. Measurement of Spectral Functions of Ultracold Atoms in Disordered Potentials Physical Review Letters, 120, pages: 060404, American Physical Society (APS), January 2018 (article)

DOI [BibTex]

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Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences

Kanagawa, M., Hennig, P., Sejdinovic, D., Sriperumbudur, B. K.

Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)

Abstract
This paper is an attempt to bridge the conceptual gaps between researchers working on the two widely used approaches based on positive definite kernels: Bayesian learning or inference using Gaussian processes on the one side, and frequentist kernel methods based on reproducing kernel Hilbert spaces on the other. It is widely known in machine learning that these two formalisms are closely related; for instance, the estimator of kernel ridge regression is identical to the posterior mean of Gaussian process regression. However, they have been studied and developed almost independently by two essentially separate communities, and this makes it difficult to seamlessly transfer results between them. Our aim is to overcome this potential difficulty. To this end, we review several old and new results and concepts from either side, and juxtapose algorithmic quantities from each framework to highlight close similarities. We also provide discussions on subtle philosophical and theoretical differences between the two approaches.

pn

arXiv [BibTex]

pn Kanagawa, M., Hennig, P., Sejdinovic, D., Sriperumbudur, B. K. Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)

arXiv [BibTex]

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Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform

Ma, L., Stueckler, J., Wu, T., Cremers, D.

arxiv, 2018, arXiv:1808.01834 (techreport)

ev

[BibTex]

ev Ma, L., Stueckler, J., Wu, T., Cremers, D. Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform arxiv, 2018, arXiv:1808.01834 (techreport)

[BibTex]

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Design and Analysis of the NIPS 2016 Review Process

Shah*, N., Tabibian*, B., Muandet, K., Guyon, I., von Luxburg, U.

Journal of Machine Learning Research, 19(49):1-34, 2018, *equal contribution (article)

ei slt

arXiv link (url) Project Page Project Page [BibTex]

ei slt Shah*, N., Tabibian*, B., Muandet, K., Guyon, I., von Luxburg, U. Design and Analysis of the NIPS 2016 Review Process Journal of Machine Learning Research, 19(49):1-34, 2018, *equal contribution (article)

arXiv link (url) Project Page Project Page [BibTex]

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A Flexible Approach for Fair Classification

Zafar, M. B., Valera, I., Gomez Rodriguez, M., Gummadi, K.

Journal of Machine Learning, 2018 (article) Accepted

ei

Project Page [BibTex]

ei Zafar, M. B., Valera, I., Gomez Rodriguez, M., Gummadi, K. A Flexible Approach for Fair Classification Journal of Machine Learning, 2018 (article) Accepted

Project Page [BibTex]

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Does universal controllability of physical systems prohibit thermodynamic cycles?

Janzing, D., Wocjan, P.

Open Systems and Information Dynamics, 25(3):1850016, 2018 (article)

ei

PDF DOI [BibTex]

ei Janzing, D., Wocjan, P. Does universal controllability of physical systems prohibit thermodynamic cycles? Open Systems and Information Dynamics, 25(3):1850016, 2018 (article)

PDF DOI [BibTex]

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Foundations of Comparison-Based Hierarchical Clustering

Ghoshdastidar, D., Perrot, M., von Luxburg, U.

2018, arXiv preprint (arXiv:1811.00928) (article)

slt

Project Page [BibTex]

slt Ghoshdastidar, D., Perrot, M., von Luxburg, U. Foundations of Comparison-Based Hierarchical Clustering 2018, arXiv preprint (arXiv:1811.00928) (article)

Project Page [BibTex]

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Analysis of Magnetic Interaction in Remotely Controlled Magnetic Devices and Its Application to a Capsule Robot for Drug Delivery

Munoz, F., Alici, G., Zhou, H., Li, W., M. Sitti,

IEEE Transactions on Magnetics, 23(1):298-310, 2018 (article)

pi

[BibTex]

pi Munoz, F., Alici, G., Zhou, H., Li, W., M. Sitti, Analysis of Magnetic Interaction in Remotely Controlled Magnetic Devices and Its Application to a Capsule Robot for Drug Delivery IEEE Transactions on Magnetics, 23(1):298-310, 2018 (article)

[BibTex]

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Numerical Quadrature for Probabilistic Policy Search

Vinogradska, J., Bischoff, B., Achterhold, J., Koller, T., Peters, J.

IEEE Transactions on Pattern Analysis and Machine Intelligence, pages: 1-1, 2018 (article)

ev

DOI [BibTex]

ev Vinogradska, J., Bischoff, B., Achterhold, J., Koller, T., Peters, J. Numerical Quadrature for Probabilistic Policy Search IEEE Transactions on Pattern Analysis and Machine Intelligence, pages: 1-1, 2018 (article)

DOI [BibTex]

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Transmission x-ray microscopy at low temperatures: Irregular supercurrent flow at small length scales

Simmendinger, J., Ruoss, S., Stahl, C., Weigand, M., Gräfe, J., Schütz, G., Albrecht, J.

{Physical Review B}, 97(13), American Physical Society, Woodbury, NY, 2018 (article)

mms

DOI [BibTex]

mms Simmendinger, J., Ruoss, S., Stahl, C., Weigand, M., Gräfe, J., Schütz, G., Albrecht, J. Transmission x-ray microscopy at low temperatures: Irregular supercurrent flow at small length scales {Physical Review B}, 97(13), American Physical Society, Woodbury, NY, 2018 (article)

DOI [BibTex]

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Combining learned and analytical models for predicting action effects

Kloss, A., Schaal, S., Bohg, J.

arXiv, 2018 (article) Submitted

Abstract
One of the most basic skills a robot should possess is predicting the effect of physical interactions with objects in the environment. This enables optimal action selection to reach a certain goal state. Traditionally, dynamics are approximated by physics-based analytical models. These models rely on specific state representations that may be hard to obtain from raw sensory data, especially if no knowledge of the object shape is assumed. More recently, we have seen learning approaches that can predict the effect of complex physical interactions directly from sensory input. It is however an open question how far these models generalize beyond their training data. In this work, we investigate the advantages and limitations of neural network based learning approaches for predicting the effects of actions based on sensory input and show how analytical and learned models can be combined to leverage the best of both worlds. As physical interaction task, we use planar pushing, for which there exists a well-known analytical model and a large real-world dataset. We propose to use a convolutional neural network to convert raw depth images or organized point clouds into a suitable representation for the analytical model and compare this approach to using neural networks for both, perception and prediction. A systematic evaluation of the proposed approach on a very large real-world dataset shows two main advantages of the hybrid architecture. Compared to a pure neural network, it significantly (i) reduces required training data and (ii) improves generalization to novel physical interaction.

am

arXiv pdf link (url) [BibTex]

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Learning Causality and Causality-Related Learning: Some Recent Progress

Zhang, K., Schölkopf, B., Spirtes, P., Glymour, C.

National Science Review, 5(1):26-29, 2018 (article)

ei

DOI [BibTex]

ei Zhang, K., Schölkopf, B., Spirtes, P., Glymour, C. Learning Causality and Causality-Related Learning: Some Recent Progress National Science Review, 5(1):26-29, 2018 (article)

DOI [BibTex]

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Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes

Alhaija, H., Mustikovela, S., Mescheder, L., Geiger, A., Rother, C.

International Journal of Computer Vision (IJCV), 2018, 2018 (article)

Abstract
The success of deep learning in computer vision is based on the availability of large annotated datasets. To lower the need for hand labeled images, virtually rendered 3D worlds have recently gained popularity. Unfortunately, creating realistic 3D content is challenging on its own and requires significant human effort. In this work, we propose an alternative paradigm which combines real and synthetic data for learning semantic instance segmentation and object detection models. Exploiting the fact that not all aspects of the scene are equally important for this task, we propose to augment real-world imagery with virtual objects of the target category. Capturing real-world images at large scale is easy and cheap, and directly provides real background appearances without the need for creating complex 3D models of the environment. We present an efficient procedure to augment these images with virtual objects. In contrast to modeling complete 3D environments, our data augmentation approach requires only a few user interactions in combination with 3D models of the target object category. Leveraging our approach, we introduce a novel dataset of augmented urban driving scenes with 360 degree images that are used as environment maps to create realistic lighting and reflections on rendered objects. We analyze the significance of realistic object placement by comparing manual placement by humans to automatic methods based on semantic scene analysis. This allows us to create composite images which exhibit both realistic background appearance as well as a large number of complex object arrangements. Through an extensive set of experiments, we conclude the right set of parameters to produce augmented data which can maximally enhance the performance of instance segmentation models. Further, we demonstrate the utility of the proposed approach on training standard deep models for semantic instance segmentation and object detection of cars in outdoor driving scenarios. We test the models trained on our augmented data on the KITTI 2015 dataset, which we have annotated with pixel-accurate ground truth, and on the Cityscapes dataset. Our experiments demonstrate that the models trained on augmented imagery generalize better than those trained on fully synthetic data or models trained on limited amounts of annotated real data.

avg

pdf Project Page [BibTex]

avg Alhaija, H., Mustikovela, S., Mescheder, L., Geiger, A., Rother, C. Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes International Journal of Computer Vision (IJCV), 2018, 2018 (article)

pdf Project Page [BibTex]

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Immersive Low-Cost Virtual Reality Treatment for Phantom Limb Pain: Evidence from Two Cases

Ambron, E., Miller, A., Kuchenbecker, K. J., Buxbaum, L. J., Coslett, H. B.

Frontiers in Neurology, 9(67):1-7, 2018 (article)

hi

DOI Project Page [BibTex]

hi Ambron, E., Miller, A., Kuchenbecker, K. J., Buxbaum, L. J., Coslett, H. B. Immersive Low-Cost Virtual Reality Treatment for Phantom Limb Pain: Evidence from Two Cases Frontiers in Neurology, 9(67):1-7, 2018 (article)

DOI Project Page [BibTex]

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Online optimal trajectory generation for robot table tennis

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

Robotics and Autonomous Systems, 105, pages: 121-137, 2018 (article)

ei

PDF link (url) DOI Project Page [BibTex]

ei Koc, O., Maeda, G., Peters, J. Online optimal trajectory generation for robot table tennis Robotics and Autonomous Systems, 105, pages: 121-137, 2018 (article)

PDF link (url) DOI Project Page [BibTex]

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Dynamics of the knowledge instinct: Effects of incoherence on the cognitive system

Schoeller, F., Eskinazi, M., Garreau, D.

Cognitive Systems Research, 2018 (article)

link (url) [BibTex]

Schoeller, F., Eskinazi, M., Garreau, D. Dynamics of the knowledge instinct: Effects of incoherence on the cognitive system Cognitive Systems Research, 2018 (article)

link (url) [BibTex]

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Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference

Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S.

Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)

Abstract
This paper introduces a novel Hilbert space representation of a counterfactual distribution---called counterfactual mean embedding (CME)---with applications in nonparametric causal inference. Counterfactual prediction has become an ubiquitous tool in machine learning applications, such as online advertisement, recommendation systems, and medical diagnosis, whose performance relies on certain interventions. To infer the outcomes of such interventions, we propose to embed the associated counterfactual distribution into a reproducing kernel Hilbert space (RKHS) endowed with a positive definite kernel. Under appropriate assumptions, the CME allows us to perform causal inference over the entire landscape of the counterfactual distribution. The CME can be estimated consistently from observational data without requiring any parametric assumption about the underlying distributions. We also derive a rate of convergence which depends on the smoothness of the conditional mean and the Radon-Nikodym derivative of the underlying marginal distributions. Our framework can deal with not only real-valued outcome, but potentially also more complex and structured outcomes such as images, sequences, and graphs. Lastly, our experimental results on off-policy evaluation tasks demonstrate the advantages of the proposed estimator.

ei pn

arXiv [BibTex]

ei pn Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S. Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)

arXiv [BibTex]

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Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models

Nishiyama, Y., Kanagawa, M., Gretton, A., Fukumizu, K.

Arxiv e-prints, arXiv:1409.5178v2 [stat.ML], 2018 (article)

Abstract
Kernel Bayesian inference is a powerful nonparametric approach to performing Bayesian inference in reproducing kernel Hilbert spaces or feature spaces. In this approach, kernel means are estimated instead of probability distributions, and these estimates can be used for subsequent probabilistic operations (as for inference in graphical models) or in computing the expectations of smooth functions, for instance. Various algorithms for kernel Bayesian inference have been obtained by combining basic rules such as the kernel sum rule (KSR), kernel chain rule, kernel product rule and kernel Bayes' rule. However, the current framework only deals with fully nonparametric inference (i.e., all conditional relations are learned nonparametrically), and it does not allow for flexible combinations of nonparametric and parametric inference, which are practically important. Our contribution is in providing a novel technique to realize such combinations. We introduce a new KSR referred to as the model-based KSR (Mb-KSR), which employs the sum rule in feature spaces under a parametric setting. Incorporating the Mb-KSR into existing kernel Bayesian framework provides a richer framework for hybrid (nonparametric and parametric) kernel Bayesian inference. As a practical application, we propose a novel filtering algorithm for state space models based on the Mb-KSR, which combines the nonparametric learning of an observation process using kernel mean embedding and the additive Gaussian noise model for a state transition process. While we focus on additive Gaussian noise models in this study, the idea can be extended to other noise models, such as the Cauchy and alpha-stable noise models.

pn

arXiv [BibTex]

pn Nishiyama, Y., Kanagawa, M., Gretton, A., Fukumizu, K. Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models Arxiv e-prints, arXiv:1409.5178v2 [stat.ML], 2018 (article)

arXiv [BibTex]

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Hierarchical Reinforcement Learning of Multiple Grasping Strategies with Human Instructions

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

Advanced Robotics, 32(18):955-968, 2018 (article)

ei

DOI Project Page [BibTex]

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Anisotropic Gold Nanostructures: Optimization via in Silico Modeling for Hyperthermia

Singh, A., Jahnke, T., Wang, S., Xiao, Y., Alapan, Y., Kharratian, S., Onbasli, M. C., Kozielski, K., David, H., Richter, G., Bill, J., Laux, P., Luch, A., Sitti, M.

ACS Applied Nano Materials, 1(11):6205-6216, 2018 (article)

pi

[BibTex]

pi Singh, A., Jahnke, T., Wang, S., Xiao, Y., Alapan, Y., Kharratian, S., Onbasli, M. C., Kozielski, K., David, H., Richter, G., Bill, J., Laux, P., Luch, A., Sitti, M. Anisotropic Gold Nanostructures: Optimization via in Silico Modeling for Hyperthermia ACS Applied Nano Materials, 1(11):6205-6216, 2018 (article)

[BibTex]

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Assessment methodology of promising porous materials for near ambient temperature hydrogen storage applications

Minuto, F. D., Balderas-Xicohténcatl, R., Policicchio, A., Hirscher, M., Agostino, R. G.

{International Journal of Hydrogen Energy}, 43(31):14550-14556, Elsevier, Amsterdam, 2018 (article)

mms

DOI [BibTex]

mms Minuto, F. D., Balderas-Xicohténcatl, R., Policicchio, A., Hirscher, M., Agostino, R. G. Assessment methodology of promising porous materials for near ambient temperature hydrogen storage applications {International Journal of Hydrogen Energy}, 43(31):14550-14556, Elsevier, Amsterdam, 2018 (article)

DOI [BibTex]

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A probabilistic model for the numerical solution of initial value problems

Schober, M., Särkkä, S., Philipp Hennig,

Statistics and Computing, Springer US, 2018 (article)

Abstract
We study connections between ordinary differential equation (ODE) solvers and probabilistic regression methods in statistics. We provide a new view of probabilistic ODE solvers as active inference agents operating on stochastic differential equation models that estimate the unknown initial value problem (IVP) solution from approximate observations of the solution derivative, as provided by the ODE dynamics. Adding to this picture, we show that several multistep methods of Nordsieck form can be recast as Kalman filtering on q-times integrated Wiener processes. Doing so provides a family of IVP solvers that return a Gaussian posterior measure, rather than a point estimate. We show that some such methods have low computational overhead, nontrivial convergence order, and that the posterior has a calibrated concentration rate. Additionally, we suggest a step size adaptation algorithm which completes the proposed method to a practically useful implementation, which we experimentally evaluate using a representative set of standard codes in the DETEST benchmark set.

pn

PDF Code DOI Project Page [BibTex]