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2018


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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)

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DOI Project Page [BibTex]

2018


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]

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]

DOI Project Page [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.

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link (url) DOI [BibTex]

link (url) DOI [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.

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link (url) DOI [BibTex]

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.

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link (url) DOI [BibTex]

link (url) DOI [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.

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link (url) DOI [BibTex]

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.

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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.

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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.

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link (url) DOI [BibTex]

link (url) DOI [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]

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]

DOI Project Page [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)

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

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

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Project Page [BibTex]

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]

PDF DOI [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)

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[BibTex]

[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]

DOI [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]

PDF link (url) DOI Project Page [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]

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)

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[BibTex]

[BibTex]


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Autofocusing-based phase correction

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

Magnetic Resonance in Medicine, 80(3):958-968, 2018 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Case series: Slowing alpha rhythm in late-stage ALS patients

Hohmann, M. R., Fomina, T., Jayaram, V., Emde, T., Just, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

Clinical Neurophysiology, 129(2):406-408, 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling

Šošić, A., Rueckert, E., Peters, J., Zoubir, A., Koeppl, H.

Journal of Machine Learning Research, 19(69):1-45, 2018 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Grip Stabilization of Novel Objects using Slip Prediction

Veiga, F., Peters, J., Hermans, T.

IEEE Transactions on Haptics, 2018 (article) In press

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Incorporation of Terbium into a Microalga Leads to Magnetotactic Swimmers

Santomauro, G., Singh, A., Park, B. W., Mohammadrahimi, M., Erkoc, P., Goering, E., Schütz, G., Sitti, M., Bill, J.

Advanced Biosystems, 2(12):1800039, 2018 (article)

mms pi

[BibTex]

[BibTex]


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Electrophysiological correlates of neurodegeneration in motor and non-motor brain regions in amyotrophic lateral sclerosis—implications for brain–computer interfacing

Kellmeyer, P., Grosse-Wentrup, M., Schulze-Bonhage, A., Ziemann, U., Ball, T.

Journal of Neural Engineering, 15(4):041003, IOP Publishing, 2018 (article)

ei

link (url) [BibTex]

link (url) [BibTex]


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Quantum machine learning: a classical perspective

Ciliberto, C., Herbster, M., Ialongo, A. D., Pontil, M., Rocchetto, A., Severini, S., Wossnig, L.

Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 474(2209):20170551, 2018 (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Kernel-based tests for joint independence

Pfister, N., Bühlmann, P., Schölkopf, B., Peters, J.

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 80(1):5-31, 2018 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Prediction of Glucose Tolerance without an Oral Glucose Tolerance Test

Babbar, R., Heni, M., Peter, A., Hrabě de Angelis, M., Häring, H., Fritsche, A., Preissl, H., Schölkopf, B., Wagner, R.

Frontiers in Endocrinology, 9, pages: 82, 2018 (article)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Invariant Models for Causal Transfer Learning

Rojas-Carulla, M., Schölkopf, B., Turner, R., Peters, J.

Journal of Machine Learning Research, 19(36):1-34, 2018 (article)

ei

link (url) [BibTex]

link (url) [BibTex]


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MOABB: Trustworthy algorithm benchmarking for BCIs

Jayaram, V., Barachant, A.

Journal of Neural Engineering, 15(6):066011, 2018 (article)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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f-Divergence constrained policy improvement

Belousov, B., Peters, J.

Journal of Machine Learning Research, 2018 (article) Submitted

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Project Page [BibTex]

Project Page [BibTex]


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Phylogenetic convolutional neural networks in metagenomics

Fioravanti*, D., Giarratano*, Y., Maggio*, V., Agostinelli, C., Chierici, M., Jurman, G., Furlanello, C.

BMC Bioinformatics, 19(2):49 pages, 2018, *equal contribution (article)

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DOI [BibTex]

DOI [BibTex]


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Food specific inhibitory control under negative mood in binge-eating disorder: Evidence from a multimethod approach

Leehr, E. J., Schag, K., Dresler, T., Grosse-Wentrup, M., Hautzinger, M., Fallgatter, A. J., Zipfel, S., Giel, K. E., Ehlis, A.

International Journal of Eating Disorders, 51(2):112-123, Wiley Online Library, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Morphological intelligence counters foot slipping in the desert locust and dynamic robots

Woodward, M. A., Sitti, M.

Proceedings of the National Academy of Sciences, 115, pages: E8358-E8367, 2018 (article)

Abstract
During dynamic terrestrial locomotion, animals use complex multifunctional feet to extract friction from the environment. However, whether roboticists assume sufficient surface friction for locomotion or actively compensate for slipping, they use relatively simple point-contact feet. We seek to understand and extract the morphological adaptations of animal feet that contribute to enhancing friction on diverse surfaces, such as the desert locust (Schistocerca gregaria) [Bennet-Clark HC (1975) J Exp Biol 63:53–83], which has both wet adhesive pads and spines. A buckling region in their knee to accommodate slipping [Bayley TG, Sutton GP, Burrows M (2012) J Exp Biol 215:1151–1161], slow nerve conduction velocity (0.5–3 m/s) [Pearson KG, Stein RB, Malhotra SK (1970) J Exp Biol 53:299–316], and an ecological pressure to enhance jumping performance for survival [Hawlena D, Kress H, Dufresne ER, Schmitz OJ (2011) Funct Ecol 25:279–288] further suggest that the locust operates near the limits of its surface friction, but without sufficient time to actively control its feet. Therefore, all surface adaptation must be through passive mechanics (morphological intelligence), which are unknown. Here, we report the slipping behavior, dynamic attachment, passive mechanics, and interplay between the spines and adhesive pads, studied through both biological and robotic experiments, which contribute to the locust’s ability to jump robustly from diverse surfaces. We found slipping to be surface-dependent and common (e.g., wood 1.32 ± 1.19 slips per jump), yet the morphological intelligence of the feet produces a significant chance to reengage the surface (e.g., wood 1.10 ± 1.13 reengagements per jump). Additionally, a discovered noncontact-type jump, further studied robotically, broadens the applicability of the morphological adaptations to both static and dynamic attachment.

pi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Three‐dimensional patterning in biomedicine: Importance and applications in neuropharmacology

Singh, A. V., Gharat, T., Batuwangala, M., Park, B. W., Endlein, T., Sitti, M.

Journal of Biomedical Materials Research Part B: Applied Biomaterials, 106(3):1369-1382, 2018 (article)

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[BibTex]

[BibTex]


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Linking imaging to omics utilizing image-guided tissue extraction

Disselhorst, J. A., Krueger, M. A., Ud-Dean, S. M. M., Bezrukov, I., Jarboui, M. A., Trautwein, C., Traube, A., Spindler, C., Cotton, J. M., Leibfritz, D., Pichler, B. J.

Proceedings of the National Academy of Sciences, 115(13):E2980-E2987, 2018 (article)

ei

DOI [BibTex]

DOI [BibTex]


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3D nanoprinted plastic kinoform x-ray optics

Sanli, U. T., Ceylan, H., Bykova, I., Weigand, M., Sitti, M., Schütz, G., Keskinbora, K.

{Advanced Materials}, 30(36), Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Discriminative Transfer Learning for General Image Restoration

Xiao, L., Heide, F., Heidrich, W., Schölkopf, B., Hirsch, M.

IEEE Transactions on Image Processing, 27(8):4091-4104, 2018 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Dissecting the synapse- and frequency-dependent network mechanisms of in vivo hippocampal sharp wave-ripples

Ramirez-Villegas, J. F., Willeke, K. F., Logothetis, N. K., Besserve, M.

Neuron, 100(5):1224-1240, 2018 (article)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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In-Hand Object Stabilization by Independent Finger Control

Veiga, F. F., Edin, B. B., Peters, J.

IEEE Transactions on Robotics, 2018 (article) Submitted

ei

Project Page [BibTex]

Project Page [BibTex]


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Visualizing and understanding Sum-Product Networks

Vergari, A., Di Mauro, N., Esposito, F.

Machine Learning, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Controllable switching between planar and helical flagellar swimming of a soft robotic sperm

Khalil, I. S. M., Tabak, A. F., Seif, M. A., Klingner, A., Sitti, M.

PloS One, 13(11):e0206456, 2018 (article)

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[BibTex]

[BibTex]