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2019


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Resource-aware IoT Control: Saving Communication through Predictive Triggering

Trimpe, S., Baumann, D.

IEEE Internet of Things Journal, 6(3):5013-5028, June 2019 (article)

Abstract
The Internet of Things (IoT) interconnects multiple physical devices in large-scale networks. When the 'things' coordinate decisions and act collectively on shared information, feedback is introduced between them. Multiple feedback loops are thus closed over a shared, general-purpose network. Traditional feedback control is unsuitable for design of IoT control because it relies on high-rate periodic communication and is ignorant of the shared network resource. Therefore, recent event-based estimation methods are applied herein for resource-aware IoT control allowing agents to decide online whether communication with other agents is needed, or not. While this can reduce network traffic significantly, a severe limitation of typical event-based approaches is the need for instantaneous triggering decisions that leave no time to reallocate freed resources (e.g., communication slots), which hence remain unused. To address this problem, novel predictive and self triggering protocols are proposed herein. From a unified Bayesian decision framework, two schemes are developed: self triggers that predict, at the current triggering instant, the next one; and predictive triggers that check at every time step, whether communication will be needed at a given prediction horizon. The suitability of these triggers for feedback control is demonstrated in hardware experiments on a cart-pole, and scalability is discussed with a multi-vehicle simulation.

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PDF arXiv DOI [BibTex]

2019


PDF arXiv DOI [BibTex]


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Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study

Neumann-Brosig, M., Marco, A., Schwarzmann, D., Trimpe, S.

IEEE Transactions on Control Systems Technology, 2019 (article) Accepted

Abstract
Bayesian optimization is proposed for automatic learning of optimal controller parameters from experimental data. A probabilistic description (a Gaussian process) is used to model the unknown function from controller parameters to a user-defined cost. The probabilistic model is updated with data, which is obtained by testing a set of parameters on the physical system and evaluating the cost. In order to learn fast, the Bayesian optimization algorithm selects the next parameters to evaluate in a systematic way, for example, by maximizing information gain about the optimum. The algorithm thus iteratively finds the globally optimal parameters with only few experiments. Taking throttle valve control as a representative industrial control example, the proposed auto-tuning method is shown to outperform manual calibration: it consistently achieves better performance with a low number of experiments. The proposed auto-tuning framework is flexible and can handle different control structures and objectives.

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arXiv (PDF) DOI Project Page [BibTex]

arXiv (PDF) DOI Project Page [BibTex]


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X-ray Optics Fabrication Using Unorthodox Approaches

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

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

mms pi

[BibTex]

[BibTex]


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Microrobotics and Microorganisms: Biohybrid Autonomous Cellular Robots

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

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

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[BibTex]

[BibTex]


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Tailored Magnetic Springs for Shape-Memory Alloy Actuated Mechanisms in Miniature Robots

Woodward, M. A., Sitti, M.

IEEE Transactions on Robotics, 35, 2019 (article)

Abstract
Animals can incorporate large numbers of actuators because of the characteristics of muscles; whereas, robots cannot, as typical motors tend to be large, heavy, and inefficient. However, shape-memory alloys (SMA), materials that contract during heating because of change in their crystal structure, provide another option. SMA, though, is unidirectional and therefore requires an additional force to reset (extend) the actuator, which is typically provided by springs or antagonistic actuation. These strategies, however, tend to limit the actuator's work output and functionality as their force-displacement relationships typically produce increasing resistive force with limited variability. In contrast, magnetic springs-composed of permanent magnets, where the interaction force between magnets mimics a spring force-have much more variable force-displacement relationships and scale well with SMA. However, as of yet, no method for designing magnetic springs for SMA-actuators has been demonstrated. Therefore, in this paper, we present a new methodology to tailor magnetic springs to the characteristics of these actuators, with experimental results both for the device and robot-integrated SMA-actuators. We found magnetic building blocks, based on sets of permanent magnets, which are well-suited to SMAs and have the potential to incorporate features such as holding force, state transitioning, friction minimization, auto-alignment, and self-mounting. We show magnetic springs that vary by more than 3 N in 750 $\mu$m and two SMA-actuated devices that allow the MultiMo-Bat to reach heights of up to 4.5 m without, and 3.6 m with, integrated gliding airfoils. Our results demonstrate the potential of this methodology to add previously impossible functionality to smart material actuators. We anticipate this methodology will inspire broader consideration of the use of magnetic springs in miniature robots and further study of the potential of tailored magnetic springs throughout mechanical systems.

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DOI [BibTex]


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Magnetically Actuated Soft Capsule Endoscope for Fine-Needle Biopsy

Son, D., Gilbert, H., Sitti, M.

Soft robotics, Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New …, 2019 (article)

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[BibTex]

[BibTex]


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Thrust and Hydrodynamic Efficiency of the Bundled Flagella

Danis, U., Rasooli, R., Chen, C., Dur, O., Sitti, M., Pekkan, K.

Micromachines, 10, 2019 (article)

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[BibTex]

[BibTex]


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Autonomous Identification and Goal-Directed Invocation of Event-Predictive Behavioral Primitives

Gumbsch, C., Butz, M. V., Martius, G.

IEEE Transactions on Cognitive and Developmental Systems, 2019 (article)

Abstract
Voluntary behavior of humans appears to be composed of small, elementary building blocks or behavioral primitives. While this modular organization seems crucial for the learning of complex motor skills and the flexible adaption of behavior to new circumstances, the problem of learning meaningful, compositional abstractions from sensorimotor experiences remains an open challenge. Here, we introduce a computational learning architecture, termed surprise-based behavioral modularization into event-predictive structures (SUBMODES), that explores behavior and identifies the underlying behavioral units completely from scratch. The SUBMODES architecture bootstraps sensorimotor exploration using a self-organizing neural controller. While exploring the behavioral capabilities of its own body, the system learns modular structures that predict the sensorimotor dynamics and generate the associated behavior. In line with recent theories of event perception, the system uses unexpected prediction error signals, i.e., surprise, to detect transitions between successive behavioral primitives. We show that, when applied to two robotic systems with completely different body kinematics, the system manages to learn a variety of complex behavioral primitives. Moreover, after initial self-exploration the system can use its learned predictive models progressively more effectively for invoking model predictive planning and goal-directed control in different tasks and environments.

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arXiv PDF video link (url) DOI Project Page [BibTex]


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The near and far of a pair of magnetic capillary disks

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

Soft Matter, 2019 (article)

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[BibTex]

[BibTex]


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Multifarious Transit Gates for Programmable Delivery of Bio‐functionalized Matters

Hu, X., Torati, S. R., Kim, H., Yoon, J., Lim, B., Kim, K., Sitti, M., Kim, C.

Small, Wiley Online Library, 2019 (article)

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[BibTex]

[BibTex]


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Multi-functional soft-bodied jellyfish-like swimming

Ren, Z., Hu, W., Dong, X., Sitti, M.

Nature communications, 10, 2019 (article)

pi

[BibTex]


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Welcome to Progress in Biomedical Engineering

Sitti, M.

Progress in Biomedical Engineering, 1, IOP Publishing, 2019 (article)

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[BibTex]

[BibTex]


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Machine Learning for Haptics: Inferring Multi-Contact Stimulation From Sparse Sensor Configuration

Sun, H., Martius, G.

Frontiers in Neurorobotics, 13, pages: 51, 2019 (article)

Abstract
Robust haptic sensation systems are essential for obtaining dexterous robots. Currently, we have solutions for small surface areas such as fingers, but affordable and robust techniques for covering large areas of an arbitrary 3D surface are still missing. Here, we introduce a general machine learning framework to infer multi-contact haptic forces on a 3D robot’s limb surface from internal deformation measured by only a few physical sensors. The general idea of this framework is to predict first the whole surface deformation pattern from the sparsely placed sensors and then to infer number, locations and force magnitudes of unknown contact points. We show how this can be done even if training data can only be obtained for single-contact points using transfer learning at the example of a modified limb of the Poppy robot. With only 10 strain-gauge sensors we obtain a high accuracy also for multiple-contact points. The method can be applied to arbitrarily shaped surfaces and physical sensor types, as long as training data can be obtained.

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link (url) DOI [BibTex]


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Fast Feedback Control over Multi-hop Wireless Networks with Mode Changes and Stability Guarantees

Baumann, D., Mager, F., Jacob, R., Thiele, L., Zimmerling, M., Trimpe, S.

ACM Transactions on Cyber-Physical Systems, 2019 (article) Accepted

ics

arXiv PDF [BibTex]

arXiv PDF [BibTex]


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Mechanics of a pressure-controlled adhesive membrane for soft robotic gripping on curved surfaces

Song, S., Drotlef, D., Paik, J., Majidi, C., Sitti, M.

Extreme Mechanics Letters, Elsevier, 2019 (article)

pi

[BibTex]


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Graphene oxide synergistically enhances antibiotic efficacy in Vancomycin resistance Staphylococcus aureus

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

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

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[BibTex]

[BibTex]


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Review of emerging concepts in nanotoxicology: opportunities and challenges for safer nanomaterial design

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

Toxicology Mechanisms and Methods, 2019 (article)

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[BibTex]

[BibTex]


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Multifunctional and biodegradable self-propelled protein motors

Pena-Francesch, A., Giltinan, J., Sitti, M.

Nature communications, 10, Nature Publishing Group, 2019 (article)

pi

[BibTex]

[BibTex]


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Cohesive self-organization of mobile microrobotic swarms

Yigit, B., Alapan, Y., Sitti, M.

arXiv preprint arXiv:1907.05856, 2019 (article)

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[BibTex]

[BibTex]


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Mobile microrobots for active therapeutic delivery

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

Advanced Therapeutics, Wiley Online Library, 2019 (article)

pi

[BibTex]

[BibTex]


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Shape-encoded dynamic assembly of mobile micromachines

Alapan, Y., Yigit, B., Beker, O., Demirörs, A. F., Sitti, M.

Nature, 18, 2019 (article)

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[BibTex]

[BibTex]


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Microfluidics Integrated Lithography‐Free Nanophotonic Biosensor for the Detection of Small Molecules

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

Advanced Optical Materials, 2019 (article)

pi

[BibTex]

[BibTex]


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ENGINEERING Bio-inspired robotic collectives

Sitti, M.

Nature, 567, pages: 314-315, Macmillan Publishers Ltd., London, England, 2019 (article)

pi

[BibTex]

[BibTex]


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Peptide-Induced Biomineralization of Tin Oxide (SnO2) Nanoparticles for Antibacterial Applications

Singh, A. V., Jahnke, T., Xiao, Y., Wang, S., Yu, Y., David, H., Richter, G., Laux, P., Luch, A., Srivastava, A., Saxena, P. S., Bill, J., Sitti, M.

Journal of nanoscience and nanotechnology, 19, American Scientific Publishers, 2019 (article)

pi

[BibTex]

[BibTex]


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Electromechanical actuation of dielectric liquid crystal elastomers for soft robotics

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

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

pi

[BibTex]

[BibTex]


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Learning to Navigate Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Gilbert, H. B., Mahmood, F., Durr, N. J., Araujo, H., Sarı, A. E., Ajay, A., Sitti, M.

IEEE Robotics and Automation Letters, 4, 2019 (article)

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[BibTex]

[BibTex]

2018


Thumb xl screenshot 2018 5 9 swimming back and forth using planar flagellar propulsion at low reynolds numbers   khalil   2018   adv ...
Swimming Back and Forth Using Planar Flagellar Propulsion at Low Reynolds Numbers

Khalil, I. S. M., Tabak, A. F., Hamed, Y., Mitwally, M. E., Tawakol, M., Klingner, A., Sitti, M.

Advanced Science, 5(2):1700461, 2018 (article)

Abstract
Abstract Peritrichously flagellated Escherichia coli swim back and forth by wrapping their flagella together in a helical bundle. However, other monotrichous bacteria cannot swim back and forth with a single flagellum and planar wave propagation. Quantifying this observation, a magnetically driven soft two‐tailed microrobot capable of reversing its swimming direction without making a U‐turn trajectory or actively modifying the direction of wave propagation is designed and developed. The microrobot contains magnetic microparticles within the polymer matrix of its head and consists of two collinear, unequal, and opposite ultrathin tails. It is driven and steered using a uniform magnetic field along the direction of motion with a sinusoidally varying orthogonal component. Distinct reversal frequencies that enable selective and independent excitation of the first or the second tail of the microrobot based on their tail length ratio are found. While the first tail provides a propulsive force below one of the reversal frequencies, the second is almost passive, and the net propulsive force achieves flagellated motion along one direction. On the other hand, the second tail achieves flagellated propulsion along the opposite direction above the reversal frequency.

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link (url) DOI [BibTex]

2018


link (url) DOI [BibTex]


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Universal Custom Complex Magnetic Spring Design Methodology

Woodward, M. A., Sitti, M.

IEEE Transactions on Magnetics, 54(1):1-13, October 2018 (article)

Abstract
A design methodology is presented for creating custom complex magnetic springs through the design of force-displacement curves. This methodology results in a magnet configuration, which will produce a desired force-displacement relationship. Initially, the problem is formulated and solved as a system of linear equations. Then, given the limited likelihood of a single solution being feasibly manufactured, key parameters of the solution are extracted and varied to create a family of solutions. Finally, these solutions are refined using numerical optimization. Given the properties of magnets, this methodology can create any well-defined function of force versus displacement and is model-independent. To demonstrate this flexibility, a number of example magnetic springs are designed; one of which, designed for use in a jumping-gliding robot's shape memory alloy actuated clutch, is manufactured and experimentally characterized. Due to the scaling of magnetic forces, the displacement region which these magnetic springs are most applicable is that of millimeters and below. However, this region is well situated for miniature robots and smart material actuators, where a tailored magnetic spring, designed to compliment a component, can enhance its performance while adding new functionality. The methodology is also expendable to variable interactions and multi-dimensional magnetic field design.

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DOI [BibTex]

DOI [BibTex]


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Programmable collective behavior in dynamically self-assembled mobile microrobotic swarms

B Yigit, , Y Alapan, , Sitti, M.

Advanced Science, July 2018 (article)

Abstract
Collective control of mobile microrobotic swarms is indispensable for their potential high-impact applications in targeted drug delivery, medical diagnostics, parallel micromanipulation, and environmental sensing and remediation. Lack of on-board computational and sensing capabilities in current microrobotic systems necessitates use of physical interactions among individual microrobots for local physical communication and cooperation. Here, we show that mobile microrobotic swarms with well-defined collective behavior can be designed by engineering magnetic interactions among individual units. Microrobots, consisting of a linear chain of self-assembled magnetic microparticles, locomote on surfaces in response to a precessing magnetic field. Control over the direction of precessing magnetic field allows engineering attractive and repulsive interactions among microrobots and, thus, collective order with well-defined spatial organization and parallel operation over macroscale distances (~ 1 cm). These microrobotic swarms can be guided through confined spaces, while preserving microrobot morphology and function. These swarms can further achieve directional transport of large cargoes on surfaces and small cargoes in bulk fluids. Described design approach, exploiting physical interactions among individual robots, enables facile and rapid formation of self-organized and reconfigurable microrobotic swarms with programmable collective order.

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link (url) [BibTex]


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3D-Printed Biodegradable Microswimmer for Drug Delivery and Targeted Cell Labeling

Hakan Ceylan, , I. Ceren Yasa, , Oncay Yasa, , Ahmet Fatih Tabak, , Joshua Giltinan, , Sitti, M.

bioRxiv, pages: 379024, July 2018 (article)

Abstract
Miniaturization of interventional medical devices can leverage minimally invasive technologies by enabling operational resolution at cellular length scales with high precision and repeatability. Untethered micron-scale mobile robots can realize this by navigating and performing in hard-to-reach, confined and delicate inner body sites. However, such a complex task requires an integrated design and engineering strategy, where powering, control, environmental sensing, medical functionality and biodegradability need to be considered altogether. The present study reports a hydrogel-based, biodegradable microrobotic swimmer, which is responsive to the changes in its microenvironment for theranostic cargo delivery and release tasks. We design a double-helical magnetic microswimmer of 20 micrometers length, which is 3D-printed with complex geometrical and compositional features. At normal physiological concentrations, matrix metalloproteinase-2 (MMP-2) enzyme can entirely degrade the microswimmer body in 118 h to solubilized non-toxic products. The microswimmer can respond to the pathological concentrations of MMP-2 by swelling and thereby accelerating the release kinetics of the drug payload. Anti-ErbB 2 antibody-tagged magnetic nanoparticles released from the degraded microswimmers serve for targeted labeling of SKBR3 breast cancer cells to realize the potential of medical imaging of local tissue sites following the therapeutic intervention. These results represent a leap forward toward clinical medical microrobots that are capable of sensing, responding to the local pathological information, and performing specific therapeutic and diagnostic tasks as orderly executed operations using their smart composite material architectures.

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DOI 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.

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arXiv PDF DOI [BibTex]

arXiv PDF DOI [BibTex]


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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.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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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.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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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.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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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.

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link (url) DOI Project Page [BibTex]


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Nonlinear decoding of a complex movie from the mammalian retina

Botella-Soler, V., Deny, S., Martius, G., Marre, O., Tkačik, G.

PLOS Computational Biology, 14(5):1-27, Public Library of Science, May 2018 (article)

Abstract
Author summary Neurons in the retina transform patterns of incoming light into sequences of neural spikes. We recorded from ∼100 neurons in the rat retina while it was stimulated with a complex movie. Using machine learning regression methods, we fit decoders to reconstruct the movie shown from the retinal output. We demonstrated that retinal code can only be read out with a low error if decoders make use of correlations between successive spikes emitted by individual neurons. These correlations can be used to ignore spontaneous spiking that would, otherwise, cause even the best linear decoders to “hallucinate” nonexistent stimuli. This work represents the first high resolution single-trial full movie reconstruction and suggests a new paradigm for separating spontaneous from stimulus-driven neural activity.

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DOI [BibTex]

DOI [BibTex]