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2018


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Intrinsic disentanglement: an invariance view for deep generative models

Besserve, M., Sun, R., Schölkopf, B.

Workshop on Theoretical Foundations and Applications of Deep Generative Models at ICML, July 2018 (conference)

ei

PDF [BibTex]

2018


PDF [BibTex]


Assessing Generative Models via Precision and Recall
Assessing Generative Models via Precision and Recall

Sajjadi, M. S. M., Bachem, O., Lucic, M., Bousquet, O., Gelly, S.

Workshop on Theoretical Foundations and Applications of Deep Generative Models (TADGM) at the 35th International Conference on Machine Learning (ICML), July 2018 (conference)

ei

arXiv [BibTex]

arXiv [BibTex]


Tempered Adversarial Networks
Tempered Adversarial Networks

Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 4448-4456, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

arXiv link (url) Project Page [BibTex]

arXiv link (url) Project Page [BibTex]


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PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

Parmas, P., Rasmussen, C., Peters, J., Doya, K.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 4065-4074, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Learning Independent Causal Mechanisms

Parascandolo, G., Kilbertus, N., Rojas-Carulla, M., Schölkopf, B.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 4033-4041, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Learning an Approximate Model Predictive Controller with Guarantees

Hertneck, M., Koehler, J., Trimpe, S., Allgöwer, F.

IEEE Control Systems Letters, 2(3):543-548, July 2018 (article)

Abstract
A supervised learning framework is proposed to approximate a model predictive controller (MPC) with reduced computational complexity and guarantees on stability and constraint satisfaction. The framework can be used for a wide class of nonlinear systems. Any standard supervised learning technique (e.g. neural networks) can be employed to approximate the MPC from samples. In order to obtain closed-loop guarantees for the learned MPC, a robust MPC design is combined with statistical learning bounds. The MPC design ensures robustness to inaccurate inputs within given bounds, and Hoeffding’s Inequality is used to validate that the learned MPC satisfies these bounds with high confidence. The result is a closed-loop statistical guarantee on stability and constraint satisfaction for the learned MPC. The proposed learning-based MPC framework is illustrated on a nonlinear benchmark problem, for which we learn a neural network controller with guarantees.

ics

arXiv PDF DOI [BibTex]

arXiv PDF DOI [BibTex]


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Nonstationary GANs: Analysis as Nonautonomous Dynamical Systems

Mehrjou, A., Schölkopf, B.

Workshop on Theoretical Foundations and Applications of Deep Generative Models at ICML, July 2018 (conference)

ei

PDF [BibTex]

PDF [BibTex]


Probabilistic Recurrent State-Space Models
Probabilistic Recurrent State-Space Models

Doerr, A., Daniel, C., Schiegg, M., Nguyen-Tuong, D., Schaal, S., Toussaint, M., Trimpe, S.

In Proceedings of the International Conference on Machine Learning (ICML), International Conference on Machine Learning (ICML), July 2018 (inproceedings)

Abstract
State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g., LSTMs) proved extremely successful in modeling complex time-series data. Fully probabilistic SSMs, however, unfortunately often prove hard to train, even for smaller problems. To overcome this limitation, we propose a scalable initialization and training algorithm based on doubly stochastic variational inference and Gaussian processes. In the variational approximation we propose in contrast to related approaches to fully capture the latent state temporal correlations to allow for robust training.

am ics

arXiv pdf Project Page [BibTex]

arXiv pdf Project Page [BibTex]


Real-time Perception meets Reactive Motion Generation
Real-time Perception meets Reactive Motion Generation

(Best Systems Paper Finalists - Amazon Robotics Best Paper Awards in Manipulation)

Kappler, D., Meier, F., Issac, J., Mainprice, J., Garcia Cifuentes, C., Wüthrich, M., Berenz, V., Schaal, S., Ratliff, N., Bohg, J.

IEEE Robotics and Automation Letters, 3(3):1864-1871, July 2018 (article)

Abstract
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. Our approach emphasizes the importance of continuous, real-time perception and its tight integration with reactive motion generation methods. We present a fully integrated system where real-time object and robot tracking as well as ambient world modeling provides the necessary input to feedback controllers and continuous motion optimizers. Specifically, they provide attractive and repulsive potentials based on which the controllers and motion optimizer can online compute movement policies at different time intervals. We extensively evaluate the proposed system on a real robotic platform in four scenarios that exhibit either challenging workspace geometry or a dynamic environment. We compare the proposed integrated system with a more traditional sense-plan-act approach that is still widely used. In 333 experiments, we show the robustness and accuracy of the proposed system.

am

arxiv video video link (url) DOI Project Page [BibTex]


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Differentially Private Database Release via Kernel Mean Embeddings

Balog, M., Tolstikhin, I., Schölkopf, B.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 423-431, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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On Matching Pursuit and Coordinate Descent

Locatello, F., Raj, A., Praneeth Karimireddy, S., Rätsch, G., Schölkopf, B., Stich, S. U., Jaggi, M.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 3204-3213, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Iterative Model-Fitting and Local Controller Optimization - Towards a Better Understanding of Convergence Properties

Wüthrich, M., Schölkopf, B.

Workshop on Prediction and Generative Modeling in Reinforcement Learning at ICML, July 2018 (conference)

ei

PDF link (url) [BibTex]

PDF 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.

Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action (CausalML) at ICML, July 2018 (conference)

ei

[BibTex]

[BibTex]


Innate turning preference of leaf-cutting ants in the absence of external orientation cues
Innate turning preference of leaf-cutting ants in the absence of external orientation cues

Endlein, T., Sitti, M.

Journal of Experimental Biology, The Company of Biologists Ltd, June 2018 (article)

Abstract
Many ants use a combination of cues for orientation but how do ants find their way when all external cues are suppressed? Do they walk in a random way or are their movements spatially oriented? Here we show for the first time that leaf-cutting ants (Acromyrmex lundii) have an innate preference of turning counter-clockwise (left) when external cues are precluded. We demonstrated this by allowing individual ants to run freely on the water surface of a newly-developed treadmill. The surface tension supported medium-sized workers but effectively prevented ants from reaching the wall of the vessel, important to avoid wall-following behaviour (thigmotaxis). Most ants ran for minutes on the spot but also slowly turned counter-clockwise in the absence of visual cues. Reconstructing the effectively walked path revealed a looping pattern which could be interpreted as a search strategy. A similar turning bias was shown for groups of ants in a symmetrical Y-maze where twice as many ants chose the left branch in the absence of optical cues. Wall-following behaviour was tested by inserting a coiled tube before the Y-fork. When ants traversed a left-coiled tube, more ants chose the left box and vice versa. Adding visual cues in form of vertical black strips either outside the treadmill or on one branch of the Y-maze led to oriented walks towards the strips. It is suggested that both, the turning bias and the wall-following are employed as search strategies for an unknown environment which can be overridden by visual cues.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Motility and chemotaxis of bacteria-driven microswimmers fabricated using antigen 43-mediated biotin display
Motility and chemotaxis of bacteria-driven microswimmers fabricated using antigen 43-mediated biotin display

Schauer, O., Mostaghaci, B., Colin, R., Hürtgen, D., Kraus, D., Sitti, M., Sourjik, V.

Scientific Reports, 8(1):9801, Nature Publishing Group, June 2018 (article)

Abstract
Bacteria-driven biohybrid microswimmers (bacteriabots) combine synthetic cargo with motile living bacteria that enable propulsion and steering. Although fabrication and potential use of such bacteriabots have attracted much attention, existing methods of fabrication require an extensive sample preparation that can drastically decrease the viability and motility of bacteria. Moreover, chemotactic behavior of bacteriabots in a liquid medium with chemical gradients has remained largely unclear. To overcome these shortcomings, we designed Escherichia coli to autonomously display biotin on its cell surface via the engineered autotransporter antigen 43 and thus to bind streptavidin-coated cargo. We show that the cargo attachment to these bacteria is greatly enhanced by motility and occurs predominantly at the cell poles, which is greatly beneficial for the fabrication of motile bacteriabots. We further performed a systemic study to understand and optimize the ability of these bacteriabots to follow chemical gradients. We demonstrate that the chemotaxis of bacteriabots is primarily limited by the cargo-dependent reduction of swimming speed and show that the fabrication of bacteriabots using elongated E. coli cells can be used to overcome this limitation.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Event-triggered Learning for Resource-efficient Networked Control
Event-triggered Learning for Resource-efficient Networked Control

Solowjow, F., Baumann, D., Garcke, J., Trimpe, S.

In Proceedings of the American Control Conference (ACC), pages: 6506 - 6512, American Control Conference, June 2018 (inproceedings)

ics

arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


Multifunctional ferrofluid-infused surfaces with reconfigurable multiscale topography
Multifunctional ferrofluid-infused surfaces with reconfigurable multiscale topography

Wang, W., Timonen, J. V. I., Carlson, A., Drotlef, D., Zhang, C. T., Kolle, S., Grinthal, A., Wong, T., Hatton, B., Kang, S. H., Kennedy, S., Chi, J., Blough, R. T., Sitti, M., Mahadevan, L., Aizenberg, J.

Nature, June 2018 (article)

Abstract
Developing adaptive materials with geometries that change in response to external stimuli provides fundamental insights into the links between the physical forces involved and the resultant morphologies and creates a foundation for technologically relevant dynamic systems1,2. In particular, reconfigurable surface topography as a means to control interfacial properties 3 has recently been explored using responsive gels 4 , shape-memory polymers 5 , liquid crystals6-8 and hybrid composites9-14, including magnetically active slippery surfaces12-14. However, these designs exhibit a limited range of topographical changes and thus a restricted scope of function. Here we introduce a hierarchical magneto-responsive composite surface, made by infiltrating a ferrofluid into a microstructured matrix (termed ferrofluid-containing liquid-infused porous surfaces, or FLIPS). We demonstrate various topographical reconfigurations at multiple length scales and a broad range of associated emergent behaviours. An applied magnetic-field gradient induces the movement of magnetic nanoparticles suspended in the ferrofluid, which leads to microscale flow of the ferrofluid first above and then within the microstructured surface. This redistribution changes the initially smooth surface of the ferrofluid (which is immobilized by the porous matrix through capillary forces) into various multiscale hierarchical topographies shaped by the size, arrangement and orientation of the confining microstructures in the magnetic field. We analyse the spatial and temporal dynamics of these reconfigurations theoretically and experimentally as a function of the balance between capillary and magnetic pressures15-19 and of the geometric anisotropy of the FLIPS system. Several interesting functions at three different length scales are demonstrated: self-assembly of colloidal particles at the micrometre scale; regulated flow of liquid droplets at the millimetre scale; and switchable adhesion and friction, liquid pumping and removal of biofilms at the centimetre scale. We envision that FLIPS could be used as part of integrated control systems for the manipulation and transport of matter, thermal management, microfluidics and fouling-release materials.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation

Ruiz, F. J. R., Valera, I., Svensson, L., Perez-Cruz, F.

IEEE Transactions on Cognitive Communications and Networking, 4(2):177-191, June 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Frame-Recurrent Video Super-Resolution
Frame-Recurrent Video Super-Resolution

Sajjadi, M. S. M., Vemulapalli, R., Brown, M.

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018 (conference)

ei

ArXiv link (url) [BibTex]

ArXiv link (url) [BibTex]


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Learning Face Deblurring Fast and Wide

Jin, M., Hirsch, M., Favaro, P.

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages: 745-753, June 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


Self-Sensing Paper Actuators Based on Graphite–Carbon Nanotube Hybrid Films
Self-Sensing Paper Actuators Based on Graphite–Carbon Nanotube Hybrid Films

Amjadi, M., Sitti, M.

Advanced Science, pages: 1800239, May 2018 (article)

Abstract
Abstract Soft actuators have demonstrated potential in a range of applications, including soft robotics, artificial muscles, and biomimetic devices. However, the majority of current soft actuators suffer from the lack of real-time sensory feedback, prohibiting their effective sensing and multitask function. Here, a promising strategy is reported to design bilayer electrothermal actuators capable of simultaneous actuation and sensation (i.e., self-sensing actuators), merely through two input electric terminals. Decoupled electrothermal stimulation and strain sensation is achieved by the optimal combination of graphite microparticles and carbon nanotubes (CNTs) in the form of hybrid films. By finely tuning the charge transport properties of hybrid films, the signal-to-noise ratio (SNR) of self-sensing actuators is remarkably enhanced to over 66. As a result, self-sensing actuators can actively track their displacement and distinguish the touch of soft and hard objects.

pi

link (url) DOI Project Page [BibTex]


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Wasserstein Auto-Encoders

Tolstikhin, I., Bousquet, O., Gelly, S., Schölkopf, B.

6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Fidelity-Weighted Learning

Dehghani, M., Mehrjou, A., Gouws, S., Kamps, J., Schölkopf, B.

6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives

Lioutikov, R., Maeda, G., Veiga, F., Kersting, K., Peters, J.

IEEE International Conference on Robotics and Automation, (ICRA), pages: 1-8, IEEE, May 2018 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Sobolev GAN

Mroueh, Y., Li*, C., Sercu*, T., Raj*, A., Cheng, Y.

6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Assisting Movement Training and Execution With Visual and Haptic Feedback

Ewerton, M., Rother, D., Weimar, J., Kollegger, G., Wiemeyer, J., Peters, J., Maeda, G.

Frontiers in Neurorobotics, 12, May 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Temporal Difference Models: Model-Free Deep RL for Model-Based Control

Pong*, V., Gu*, S., Dalal, M., Levine, S.

6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I.

Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning

Eysenbach, B., Gu, S., Ibarz, J., Levine, S.

6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

Videos link (url) Project Page [BibTex]

Videos link (url) Project Page [BibTex]


Online Learning of a Memory for Learning Rates
Online Learning of a Memory for Learning Rates

(nominated for best paper award)

Meier, F., Kappler, D., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018, accepted (inproceedings)

Abstract
The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning tasks. Here, we introduce a computationally efficient online meta-learning algorithm that builds and optimizes a memory model of the optimal learning rate landscape from previously observed gradient behaviors. While performing task specific optimization, this memory of learning rates predicts how to scale currently observed gradients. After applying the gradient scaling our meta-learner updates its internal memory based on the observed effect its prediction had. Our meta-learner can be combined with any gradient-based optimizer, learns on the fly and can be transferred to new optimization tasks. In our evaluations we show that our meta-learning algorithm speeds up learning of MNIST classification and a variety of learning control tasks, either in batch or online learning settings.

am

pdf video code [BibTex]

pdf video code [BibTex]


Tempered Adversarial Networks
Tempered Adversarial Networks

Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B.

Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

arXiv [BibTex]

arXiv [BibTex]


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Learning Coupled Forward-Inverse Models with Combined Prediction Errors

Koert, D., Maeda, G., Neumann, G., Peters, J.

IEEE International Conference on Robotics and Automation, (ICRA), pages: 2433-2439, IEEE, May 2018 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Learning Disentangled Representations with Wasserstein Auto-Encoders

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I.

Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Automatic Estimation of Modulation Transfer Functions

Bauer, M., Volchkov, V., Hirsch, M., Schölkopf, B.

IEEE International Conference on Computational Photography (ICCP), May 2018 (conference)

ei sf

DOI [BibTex]

DOI [BibTex]


Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks
Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks

Sutanto, G., Su, Z., Schaal, S., Meier, F.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018 (inproceedings)

am

pdf video [BibTex]

pdf video [BibTex]


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Causal Discovery Using Proxy Variables

Rojas-Carulla, M., Baroni, M., Lopez-Paz, D.

Workshop at 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences

Pinsler, R., Akrour, R., Osa, T., Peters, J., Neumann, G.

IEEE International Conference on Robotics and Automation, (ICRA), pages: 596-601, IEEE, May 2018 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Group invariance principles for causal generative models

Besserve, M., Shajarisales, N., Schölkopf, B., Janzing, D.

Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 557-565, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Boosting Variational Inference: an Optimization Perspective

Locatello, F., Khanna, R., Ghosh, J., Rätsch, G.

Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 464-472, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

ei

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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Mixture of Attractors: A Novel Movement Primitive Representation for Learning Motor Skills From Demonstrations

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

IEEE Robotics and Automation Letters, 3(2):926-933, April 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Soft erythrocyte-based bacterial microswimmers for cargo delivery
Soft erythrocyte-based bacterial microswimmers for cargo delivery

Alapan, Y., Yasa, O., Schauer, O., Giltinan, J., Tabak, A. F., Sourjik, V., Sitti, M.

Science Robotics, 3(17):eaar4423, Science Robotics, April 2018 (article)

Abstract
Bacteria-propelled biohybrid microswimmers have recently shown to be able to actively transport and deliver cargos encapsulated into their synthetic constructs to specific regions locally. However, usage of synthetic materials as cargo carriers can result in inferior performance in load-carrying efficiency, biocompatibility, and biodegradability, impeding clinical translation of biohybrid microswimmers. Here, we report construction and external guidance of bacteria-driven microswimmers using red blood cells (RBCs; erythrocytes) as autologous cargo carriers for active and guided drug delivery. Multifunctional biohybrid microswimmers were fabricated by attachment of RBCs [loaded with anticancer doxorubicin drug molecules and superparamagnetic iron oxide nanoparticles (SPIONs)] to bioengineered motile bacteria, Escherichia coli MG1655, via biotin-avidin-biotin binding complex. Autonomous and on-board propulsion of biohybrid microswimmers was provided by bacteria, and their external magnetic guidance was enabled by SPIONs loaded into the RBCs. Furthermore, bacteria-driven RBC microswimmers displayed preserved deformability and attachment stability even after squeezing in microchannels smaller than their sizes, as in the case of bare RBCs. In addition, an on-demand light-activated hyperthermia termination switch was engineered for RBC microswimmers to control bacteria population after operations. RBCs, as biological and autologous cargo carriers in the biohybrid microswimmers, offer notable advantages in stability, deformability, biocompatibility, and biodegradability over synthetic cargo-carrier materials. The biohybrid microswimmer design presented here transforms RBCs from passive cargo carriers into active and guidable cargo carriers toward targeted drug and other cargo delivery applications in medicine.

pi

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

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


Evaluating Low-Power Wireless Cyber-Physical Systems
Evaluating Low-Power Wireless Cyber-Physical Systems

Baumann, D., Mager, F., Singh, H., Zimmerling, M., Trimpe, S.

In Proceedings of the IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), pages: 13-18, IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), April 2018 (inproceedings)

ics

arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


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Miniature soft robots – road to the clinic

Sitti, M.

Nature Reviews Materials, April 2018 (article)

Abstract
Soft small robots offer the opportunity to non-invasively access human tissue to perform medical operations and deliver drugs; however, challenges in materials design, biocompatibility and function control remain to be overcome for soft robots to reach the clinic.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic movement primitives under unknown system dynamics

Paraschos, A., Rueckert, E., Peters, J., Neumann, G.

Advanced Robotics, 32(6):297-310, April 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Cause-Effect Inference by Comparing Regression Errors

Blöbaum, P., Janzing, D., Washio, T., Shimizu, S., Schölkopf, B.

Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) , 84, pages: 900-909, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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


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

link (url) [BibTex]


Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots
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]

link (url) [BibTex]


Self‐Folded Hydrogel Tubes for Implantable Muscular Tissue Scaffolds
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.

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link (url) DOI [BibTex]


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

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link (url) DOI [BibTex]

link (url) DOI [BibTex]