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2017


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The Numerics of GANs

Mescheder, L., Nowozin, S., Geiger, A.

In Proceedings from the conference "Neural Information Processing Systems 2017., (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (inproceedings)

Abstract
In this paper, we analyze the numerics of common algorithms for training Generative Adversarial Networks (GANs). Using the formalism of smooth two-player games we analyze the associated gradient vector field of GAN training objectives. Our findings suggest that the convergence of current algorithms suffers due to two factors: i) presence of eigenvalues of the Jacobian of the gradient vector field with zero real-part, and ii) eigenvalues with big imaginary part. Using these findings, we design a new algorithm that overcomes some of these limitations and has better convergence properties. Experimentally, we demonstrate its superiority on training common GAN architectures and show convergence on GAN architectures that are known to be notoriously hard to train.

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pdf Project Page [BibTex]

2017


pdf Project Page [BibTex]


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Soft Actuators for Small-Scale Robotics

Hines, L., Petersen, K., Lum, G. Z., Sitti, M.

Advanced Materials, 2017 (article)

Abstract
This review comprises a detailed survey of ongoing methodologies for soft actuators, highlighting approaches suitable for nanometer- to centimeter-scale robotic applications. Soft robots present a special design challenge in that their actuation and sensing mechanisms are often highly integrated with the robot body and overall functionality. When less than a centimeter, they belong to an even more special subcategory of robots or devices, in that they often lack on-board power, sensing, computation, and control. Soft, active materials are particularly well suited for this task, with a wide range of stimulants and a number of impressive examples, demonstrating large deformations, high motion complexities, and varied multifunctionality. Recent research includes both the development of new materials and composites, as well as novel implementations leveraging the unique properties of soft materials.

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DOI [BibTex]


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A deep learning based fusion of RGB camera information and magnetic localization information for endoscopic capsule robots

Turan, M., Shabbir, J., Araujo, H., Konukoglu, E., Sitti, M.

International Journal of Intelligent Robotics and Applications, 1(4):442-450, December 2017 (article)

Abstract
A reliable, real time localization functionality is crutial for actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagnostic and therapeutic technology for the gastrointestinal (GI) tract. In this study, we extend the success of deep learning approaches from various research fields to the problem of sensor fusion for endoscopic capsule robots. We propose a multi-sensor fusion based localization approach which combines endoscopic camera information and magnetic sensor based localization information. The results performed on real pig stomach dataset show that our method achieves sub-millimeter precision for both translational and rotational movements.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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3D Chemical Patterning of Micromaterials for Encoded Functionality

Ceylan, H., Yasa, I. C., Sitti, M.

Advanced Materials, 2017 (article)

Abstract
Programming local chemical properties of microscale soft materials with 3D complex shapes is indispensable for creating sophisticated functionalities, which has not yet been possible with existing methods. Precise spatiotemporal control of two-photon crosslinking is employed as an enabling tool for 3D patterning of microprinted structures for encoding versatile chemical moieties.

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DOI Project Page [BibTex]


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Biohybrid actuators for robotics: A review of devices actuated by living cells

Ricotti, L., Trimmer, B., Feinberg, A. W., Raman, R., Parker, K. K., Bashir, R., Sitti, M., Martel, S., Dario, P., Menciassi, A.

Science Robotics, 2(12), Science Robotics, November 2017 (article)

Abstract
Actuation is essential for artificial machines to interact with their surrounding environment and to accomplish the functions for which they are designed. Over the past few decades, there has been considerable progress in developing new actuation technologies. However, controlled motion still represents a considerable bottleneck for many applications and hampers the development of advanced robots, especially at small length scales. Nature has solved this problem using molecular motors that, through living cells, are assembled into multiscale ensembles with integrated control systems. These systems can scale force production from piconewtons up to kilonewtons. By leveraging the performance of living cells and tissues and directly interfacing them with artificial components, it should be possible to exploit the intricacy and metabolic efficiency of biological actuation within artificial machines. We provide a survey of important advances in this biohybrid actuation paradigm.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?

Behl, A., Jafari, O. H., Mustikovela, S. K., Alhaija, H. A., Rother, C., Geiger, A.

In Proceedings IEEE International Conference on Computer Vision (ICCV), IEEE, Piscataway, NJ, USA, IEEE International Conference on Computer Vision (ICCV), October 2017 (inproceedings)

Abstract
Existing methods for 3D scene flow estimation often fail in the presence of large displacement or local ambiguities, e.g., at texture-less or reflective surfaces. However, these challenges are omnipresent in dynamic road scenes, which is the focus of this work. Our main contribution is to overcome these 3D motion estimation problems by exploiting recognition. In particular, we investigate the importance of recognition granularity, from coarse 2D bounding box estimates over 2D instance segmentations to fine-grained 3D object part predictions. We compute these cues using CNNs trained on a newly annotated dataset of stereo images and integrate them into a CRF-based model for robust 3D scene flow estimation - an approach we term Instance Scene Flow. We analyze the importance of each recognition cue in an ablation study and observe that the instance segmentation cue is by far strongest, in our setting. We demonstrate the effectiveness of our method on the challenging KITTI 2015 scene flow benchmark where we achieve state-of-the-art performance at the time of submission.

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pdf suppmat Poster Project Page [BibTex]

pdf suppmat Poster Project Page [BibTex]


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Sparsity Invariant CNNs

Uhrig, J., Schneider, N., Schneider, L., Franke, U., Brox, T., Geiger, A.

International Conference on 3D Vision (3DV) 2017, International Conference on 3D Vision (3DV), October 2017 (conference)

Abstract
In this paper, we consider convolutional neural networks operating on sparse inputs with an application to depth upsampling from sparse laser scan data. First, we show that traditional convolutional networks perform poorly when applied to sparse data even when the location of missing data is provided to the network. To overcome this problem, we propose a simple yet effective sparse convolution layer which explicitly considers the location of missing data during the convolution operation. We demonstrate the benefits of the proposed network architecture in synthetic and real experiments \wrt various baseline approaches. Compared to dense baselines, the proposed sparse convolution network generalizes well to novel datasets and is invariant to the level of sparsity in the data. For our evaluation, we derive a novel dataset from the KITTI benchmark, comprising 93k depth annotated RGB images. Our dataset allows for training and evaluating depth upsampling and depth prediction techniques in challenging real-world settings.

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pdf suppmat Project Page Project Page [BibTex]

pdf suppmat Project Page Project Page [BibTex]


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OctNetFusion: Learning Depth Fusion from Data

Riegler, G., Ulusoy, A. O., Bischof, H., Geiger, A.

International Conference on 3D Vision (3DV) 2017, International Conference on 3D Vision (3DV), October 2017 (conference)

Abstract
In this paper, we present a learning based approach to depth fusion, i.e., dense 3D reconstruction from multiple depth images. The most common approach to depth fusion is based on averaging truncated signed distance functions, which was originally proposed by Curless and Levoy in 1996. While this method is simple and provides great results, it is not able to reconstruct (partially) occluded surfaces and requires a large number frames to filter out sensor noise and outliers. Motivated by the availability of large 3D model repositories and recent advances in deep learning, we present a novel 3D CNN architecture that learns to predict an implicit surface representation from the input depth maps. Our learning based method significantly outperforms the traditional volumetric fusion approach in terms of noise reduction and outlier suppression. By learning the structure of real world 3D objects and scenes, our approach is further able to reconstruct occluded regions and to fill in gaps in the reconstruction. We demonstrate that our learning based approach outperforms both vanilla TSDF fusion as well as TV-L1 fusion on the task of volumetric fusion. Further, we demonstrate state-of-the-art 3D shape completion results.

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pdf Video 1 Video 2 Project Page Project Page [BibTex]

pdf Video 1 Video 2 Project Page Project Page [BibTex]


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Editorial for the Special Issue on Microdevices and Microsystems for Cell Manipulation

Hu, W., Ohta, A. T.

8, Multidisciplinary Digital Publishing Institute, September 2017 (misc)

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DOI [BibTex]

DOI [BibTex]


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Multifunctional Bacteria-Driven Microswimmers for Targeted Active Drug Delivery

Park, B., Zhuang, J., Yasa, O., Sitti, M.

ACS Nano, 11(9):8910-8923, September 2017, PMID: 28873304 (article)

Abstract
High-performance, multifunctional bacteria-driven microswimmers are introduced using an optimized design and fabrication method for targeted drug delivery applications. These microswimmers are made of mostly single Escherichia coli bacterium attached to the surface of drug-loaded polyelectrolyte multilayer (PEM) microparticles with embedded magnetic nanoparticles. The PEM drug carriers are 1 μm in diameter and are intentionally fabricated with a more viscoelastic material than the particles previously studied in the literature. The resulting stochastic microswimmers are able to swim at mean speeds of up to 22.5 μm/s. They can be guided and targeted to specific cells, because they exhibit biased and directional motion under a chemoattractant gradient and a magnetic field, respectively. Moreover, we demonstrate the microswimmers delivering doxorubicin anticancer drug molecules, encapsulated in the polyelectrolyte multilayers, to 4T1 breast cancer cells under magnetic guidance in vitro. The results reveal the feasibility of using these active multifunctional bacteria-driven microswimmers to perform targeted drug delivery with significantly enhanced drug transfer, when compared with the passive PEM microparticles.

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link (url) DOI Project Page [BibTex]


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EndoSensorFusion: Particle Filtering-Based Multi-sensory Data Fusion with Switching State-Space Model for Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Gilbert, H., Araujo, H., Cemgil, T., Sitti, M.

ArXiv e-prints, September 2017 (article)

Abstract
A reliable, real time multi-sensor fusion functionality is crucial for localization of actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagnostic and therapeutic technology for the gastrointestinal (GI) tract. In this study, we propose a novel multi-sensor fusion approach based on a particle filter that incorporates an online estimation of sensor reliability and a non-linear kinematic model learned by a recurrent neural network. Our method sequentially estimates the true robot pose from noisy pose observations delivered by multiple sensors. We experimentally test the method using 5 degree-of-freedom (5-DoF) absolute pose measurement by a magnetic localization system and a 6-DoF relative pose measurement by visual odometry. In addition, the proposed method is capable of detecting and handling sensor failures by ignoring corrupted data, providing the robustness expected of a medical device. Detailed analyses and evaluations are presented using ex-vivo experiments on a porcine stomach model prove that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories.

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link (url) Project Page [BibTex]


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Direct Visual Odometry for a Fisheye-Stereo Camera

Liu, P., Heng, L., Sattler, T., Geiger, A., Pollefeys, M.

In Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Piscataway, NJ, USA, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2017 (inproceedings)

Abstract
We present a direct visual odometry algorithm for a fisheye-stereo camera. Our algorithm performs simultaneous camera motion estimation and semi-dense reconstruction. The pipeline consists of two threads: a tracking thread and a mapping thread. In the tracking thread, we estimate the camera pose via semi-dense direct image alignment. To have a wider field of view (FoV) which is important for robotic perception, we use fisheye images directly without converting them to conventional pinhole images which come with a limited FoV. To address the epipolar curve problem, plane-sweeping stereo is used for stereo matching and depth initialization. Multiple depth hypotheses are tracked for selected pixels to better capture the uncertainty characteristics of stereo matching. Temporal motion stereo is then used to refine the depth and remove false positive depth hypotheses. Our implementation runs at an average of 20 Hz on a low-end PC. We run experiments in outdoor environments to validate our algorithm, and discuss the experimental results. We experimentally show that we are able to estimate 6D poses with low drift, and at the same time, do semi-dense 3D reconstruction with high accuracy.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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Endo-VMFuseNet: Deep Visual-Magnetic Sensor Fusion Approach for Uncalibrated, Unsynchronized and Asymmetric Endoscopic Capsule Robot Localization Data

Turan, M., Almalioglu, Y., Gilbert, H., Eren Sari, A., Soylu, U., Sitti, M.

ArXiv e-prints, September 2017 (article)

Abstract
In the last decade, researchers and medical device companies have made major advances towards transforming passive capsule endoscopes into active medical robots. One of the major challenges is to endow capsule robots with accurate perception of the environment inside the human body, which will provide necessary information and enable improved medical procedures. We extend the success of deep learning approaches from various research fields to the problem of uncalibrated, asynchronous, and asymmetric sensor fusion for endoscopic capsule robots. The results performed on real pig stomach datasets show that our method achieves sub-millimeter precision for both translational and rotational movements and contains various advantages over traditional sensor fusion techniques.

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link (url) Project Page [BibTex]


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Magnetotactic Bacteria Powered Biohybrids Target E. coli Biofilms

Stanton, M. M., Park, B., Vilela, D., Bente, K., Faivre, D., Sitti, M., Sánchez, S.

ACS Nano, 0(0):null, September 2017, PMID: 28933815 (article)

Abstract
Biofilm colonies are typically resistant to general antibiotic treatment and require targeted methods for their removal. One of these methods includes the use of nanoparticles as carriers for antibiotic delivery, where they randomly circulate in fluid until they make contact with the infected areas. However, the required proximity of the particles to the biofilm results in only moderate efficacy. We demonstrate here that the nonpathogenic magnetotactic bacteria Magnetosopirrillum gryphiswalense (MSR-1) can be integrated with drug-loaded mesoporous silica microtubes to build controllable microswimmers (biohybrids) capable of antibiotic delivery to target an infectious biofilm. Applying external magnetic guidance capability and swimming power of the MSR-1 cells, the biohybrids are directed to and forcefully pushed into matured Escherichia coli (E. coli) biofilms. Release of the antibiotic, ciprofloxacin, is triggered by the acidic microenvironment of the biofilm, ensuring an efficient drug delivery system. The results reveal the capabilities of a nonpathogenic bacteria species to target and dismantle harmful biofilms, indicating biohybrid systems have great potential for antibiofilm applications.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Augmented Reality Meets Deep Learning for Car Instance Segmentation in Urban Scenes

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

In Proceedings of the British Machine Vision Conference 2017, Proceedings of the British Machine Vision Conference, September 2017 (inproceedings)

Abstract
The success of deep learning in computer vision is based on the availability of large annotated datasets. To lower the need for hand labeled images, virtually rendered 3D worlds have recently gained popularity. Unfortunately, creating realistic 3D content is challenging on its own and requires significant human effort. In this work, we propose an alternative paradigm which combines real and synthetic data for learning semantic instance segmentation models. Exploiting the fact that not all aspects of the scene are equally important for this task, we propose to augment real-world imagery with virtual objects of the target category. Capturing real-world images at large scale is easy and cheap, and directly provides real background appearances without the need for creating complex 3D models of the environment. We present an efficient procedure to augment these images with virtual objects. This allows us to create realistic composite images which exhibit both realistic background appearance as well as a large number of complex object arrangements. In contrast to modeling complete 3D environments, our data augmentation approach requires only a few user interactions in combination with 3D shapes of the target object category. We demonstrate the utility of the proposed approach for training a state-of-the-art high-capacity deep model for semantic instance segmentation. In particular, we consider the task of segmenting car instances on the KITTI dataset which we have annotated with pixel-accurate ground truth. Our experiments demonstrate that models trained on augmented imagery generalize better than those trained on synthetic data or models trained on limited amounts of annotated real data.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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Swimming in low reynolds numbers using planar and helical flagellar waves

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

In International Conference on Intelligent Robots and Systems (IROS) 2017, pages: 1907-1912, International Conference on Intelligent Robots and Systems, September 2017 (inproceedings)

Abstract
In travelling towards the oviducts, sperm cells undergo transitions between planar to helical flagellar propulsion by a beating tail based on the viscosity of the environment. In this work, we aim to model and mimic this behaviour in low Reynolds number fluids using externally actuated soft robotic sperms. We numerically investigate the effects of transition between planar to helical flagellar propulsion on the swimming characteristics of the robotic sperm using a model based on resistive-force theory to study the role of viscous forces on its flexible tail. Experimental results are obtained using robots that contain magnetic particles within the polymer matrix of its head and an ultra-thin flexible tail. The planar and helical flagellar propulsion are achieved using in-plane and out-of-plane uniform fields with sinusoidally varying components, respectively. We experimentally show that the swimming speed of the robotic sperm increases by a factor of 1.4 (fluid viscosity 5 Pa.s) when it undergoes a controlled transition between planar to helical flagellar propulsion, at relatively low actuation frequencies.

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DOI [BibTex]

DOI [BibTex]


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Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks

Mescheder, L., Nowozin, S., Geiger, A.

In Proceedings of the 34th International Conference on Machine Learning, 70, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (inproceedings)

Abstract
Variational Autoencoders (VAEs) are expressive latent variable models that can be used to learn complex probability distributions from training data. However, the quality of the resulting model crucially relies on the expressiveness of the inference model. We introduce Adversarial Variational Bayes (AVB), a technique for training Variational Autoencoders with arbitrarily expressive inference models. We achieve this by introducing an auxiliary discriminative network that allows to rephrase the maximum-likelihood-problem as a two-player game, hence establishing a principled connection between VAEs and Generative Adversarial Networks (GANs). We show that in the nonparametric limit our method yields an exact maximum-likelihood assignment for the parameters of the generative model, as well as the exact posterior distribution over the latent variables given an observation. Contrary to competing approaches which combine VAEs with GANs, our approach has a clear theoretical justification, retains most advantages of standard Variational Autoencoders and is easy to implement.

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pdf suppmat Project Page arxiv-version Project Page [BibTex]

pdf suppmat Project Page arxiv-version Project Page [BibTex]


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Sparse-then-Dense Alignment based 3D Map Reconstruction Method for Endoscopic Capsule Robots

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

ArXiv e-prints, August 2017 (article)

Abstract
Since the development of capsule endoscopcy technology, substantial progress were made in converting passive capsule endoscopes to robotic active capsule endoscopes which can be controlled by the doctor. However, robotic capsule endoscopy still has some challenges. In particular, the use of such devices to generate a precise and globally consistent three-dimensional (3D) map of the entire inner organ remains an unsolved problem. Such global 3D maps of inner organs would help doctors to detect the location and size of diseased areas more accurately, precisely, and intuitively, thus permitting more accurate and intuitive diagnoses. The proposed 3D reconstruction system is built in a modular fashion including preprocessing, frame stitching, and shading-based 3D reconstruction modules. We propose an efficient scheme to automatically select the key frames out of the huge quantity of raw endoscopic images. Together with a bundle fusion approach that aligns all the selected key frames jointly in a globally consistent way, a significant improvement of the mosaic and 3D map accuracy was reached. To the best of our knowledge, this framework is the first complete pipeline for an endoscopic capsule robot based 3D map reconstruction containing all of the necessary steps for a reliable and accurate endoscopic 3D map. For the qualitative evaluations, a real pig stomach is employed. Moreover, for the first time in literature, a detailed and comprehensive quantitative analysis of each proposed pipeline modules is performed using a non-rigid esophagus gastro duodenoscopy simulator, four different endoscopic cameras, a magnetically activated soft capsule robot (MASCE), a sub-millimeter precise optical motion tracker and a fine-scale 3D optical scanner.

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Dipole codes attractively encode glue functions

Ipparthi, D., Mastrangeli, M., Winslow, A.

Theoretical Computer Science, 671, pages: 19 - 25, August 2017, Computational Self-Assembly (article)

Abstract
Dipole words are sequences of magnetic dipoles, in which alike elements repel and opposite elements attract. Magnetic dipoles contrast with more general sets of bonding types, called glues, in which pairwise bonding strength is specified by a glue function. We prove that every glue function g has a set of dipole words, called a dipole code, that attractively encodes g: the pairwise attractions (positive or non-positive bond strength) between the words are identical to those of g. Moreover, we give such word sets of asymptotically optimal length. Similar results are obtained for a commonly used subclass of glue functions.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning local feature aggregation functions with backpropagation

Paschalidou, D., Katharopoulos, A., Diou, C., Delopoulos, A.

In IEEE, Signal Processing Conference (EUSIPCO), 25th European, August 2017 (inproceedings)

Abstract
This paper introduces a family of local feature aggregation functions and a novel method to estimate their parameters, such that they generate optimal representations for classification (or any task that can be expressed as a cost function minimization problem). To achieve that, we compose the local feature aggregation function with the classifier cost function and we backpropagate the gradient of this cost function in order to update the local feature aggregation function parameters. Experiments on synthetic datasets indicate that our method discovers parameters that model the class-relevant information in addition to the local feature space. Further experiments on a variety of motion and visual descriptors, both on image and video datasets, show that our method outperforms other state-of-the-art local feature aggregation functions, such as Bag of Words, Fisher Vectors and VLAD, by a large margin.

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pdf code poster link (url) DOI [BibTex]

pdf code poster link (url) DOI [BibTex]


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Hypoxia‐enhanced adhesion of red blood cells in microscale flow

Kim, M., Alapan, Y., Adhikari, A., Little, J. A., Gurkan, U. A.

Microcirculation, 24(5):e12374, July 2017 (article)

Abstract
Abstract Objectives The advancement of microfluidic technology has facilitated the simulation of physiological conditions of the microcirculation, such as oxygen tension, fluid flow, and shear stress in these devices. Here, we present a micro‐gas exchanger integrated with microfluidics to study RBC adhesion under hypoxic flow conditions mimicking postcapillary venules. Methods We simulated a range of physiological conditions and explored RBC adhesion to endothelial or subendothelial components (FN or LN). Blood samples were injected into microchannels at normoxic or hypoxic physiological flow conditions. Quantitative evaluation of RBC adhesion was performed on 35 subjects with homozygous SCD. Results Significant heterogeneity in RBC adherence response to hypoxia was seen among SCD patients. RBCs from a HEA population showed a significantly greater increase in adhesion compared to RBCs from a HNA population, for both FN and LN. Conclusions The approach presented here enabled the control of oxygen tension in blood during microscale flow and the quantification of RBC adhesion in a cost‐efficient and patient‐specific manner. We identified a unique patient population in which RBCs showed enhanced adhesion in hypoxia in vitro. Clinical correlates suggest a more severe clinical phenotype in this subgroup.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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An XY ϴz flexure mechanism with optimal stiffness properties

Lum, G. Z., Pham, M. T., Teo, T. J., Yang, G., Yeo, S. H., Sitti, M.

In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pages: 1103-1110, July 2017 (inproceedings)

Abstract
The development of optimal XY θz flexure mechanisms, which can deliver high precision motion about the z-axis, and along the x- and y-axes is highly desirable for a wide range of micro/nano-positioning tasks pertaining to biomedical research, microscopy technologies and various industrial applications. Although maximizing the stiffness ratios is a very critical design requirement, the achievable translational and rotational stiffness ratios of existing XY θz flexure mechanisms are still restricted between 0.5 and 130. As a result, these XY θz flexure mechanisms are unable to fully optimize their workspace and capabilities to reject disturbances. Here, we present an optimal XY θz flexure mechanism, which is designed to have maximum stiffness ratios. Based on finite element analysis (FEA), it has translational stiffness ratio of 248, rotational stiffness ratio of 238 and a large workspace of 2.50 mm × 2.50 mm × 10°. Despite having such a large workspace, FEA also predicts that the proposed mechanism can still achieve a high bandwidth of 70 Hz. In comparison, the bandwidth of similar existing flexure mechanisms that can deflect more than 0.5 mm or 0.5° is typically less than 45 Hz. Hence, the high stiffness ratios of the proposed mechanism are achieved without compromising its dynamic performance. Preliminary experimental results pertaining to the mechanism's translational actuating stiffness and bandwidth were in agreement with the FEA predictions as the deviation was within 10%. In conclusion, the proposed flexure mechanism exhibits superior performance and can be used across a wide range of applications.

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DOI [BibTex]

DOI [BibTex]


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Positioning of drug carriers using permanent magnet-based robotic system in three-dimensional space

Khalil, I. S. M., Alfar, A., Tabak, A. F., Klingner, A., Stramigioli, S., Sitti, M.

In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pages: 1117-1122, July 2017 (inproceedings)

Abstract
Magnetic control of drug carriers using systems with open-configurations is essential to enable scaling to the size of in vivo applications. In this study, we demonstrate motion control of paramagnetic microparticles in a low Reynolds number fluid, using a permanent magnet-based robotic system with an open-configuration. The microparticles are controlled in three-dimensional (3D) space using a cylindrical NdFeB magnet that is fixed to the end-effector of a robotic arm. We develop a kinematic map between the position of the microparticles and the configuration of the robotic arm, and use this map as a basis of a closed-loop control system based on the position of the microparticles. Our experimental results show the ability of the robot configuration to control the exerted field gradient on the dipole of the microparticles, and achieve positioning in 3D space with maximum error of 300 µm and 600 µm in the steady-state during setpoint and trajectory tracking, respectively.

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DOI [BibTex]

DOI [BibTex]


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Self-assembly of micro/nanosystems across scales and interfaces

Mastrangeli, M.

In 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), pages: 676 - 681, IEEE, July 2017 (inproceedings)

Abstract
Steady progress in understanding and implementation are establishing self-assembly as a versatile, parallel and scalable approach to the fabrication of transducers. In this contribution, I illustrate the principles and reach of self-assembly with three applications at different scales - namely, the capillary self-alignment of millimetric components, the sealing of liquid-filled polymeric microcapsules, and the accurate capillary assembly of single nanoparticles - and propose foreseeable directions for further developments.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data

Janai, J., Güney, F., Wulff, J., Black, M., Geiger, A.

In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 1406-1416, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (inproceedings)

Abstract
Existing optical flow datasets are limited in size and variability due to the difficulty of capturing dense ground truth. In this paper, we tackle this problem by tracking pixels through densely sampled space-time volumes recorded with a high-speed video camera. Our model exploits the linearity of small motions and reasons about occlusions from multiple frames. Using our technique, we are able to establish accurate reference flow fields outside the laboratory in natural environments. Besides, we show how our predictions can be used to augment the input images with realistic motion blur. We demonstrate the quality of the produced flow fields on synthetic and real-world datasets. Finally, we collect a novel challenging optical flow dataset by applying our technique on data from a high-speed camera and analyze the performance of the state-of-the-art in optical flow under various levels of motion blur.

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pdf suppmat Project page Video DOI Project Page [BibTex]

pdf suppmat Project page Video DOI Project Page [BibTex]


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OctNet: Learning Deep 3D Representations at High Resolutions

Riegler, G., Ulusoy, O., Geiger, A.

In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (inproceedings)

Abstract
We present OctNet, a representation for deep learning with sparse 3D data. In contrast to existing models, our representation enables 3D convolutional networks which are both deep and high resolution. Towards this goal, we exploit the sparsity in the input data to hierarchically partition the space using a set of unbalanced octrees where each leaf node stores a pooled feature representation. This allows to focus memory allocation and computation to the relevant dense regions and enables deeper networks without compromising resolution. We demonstrate the utility of our OctNet representation by analyzing the impact of resolution on several 3D tasks including 3D object classification, orientation estimation and point cloud labeling.

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pdf suppmat Project Page Video Project Page [BibTex]

pdf suppmat Project Page Video Project Page [BibTex]


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A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos

Schöps, T., Schönberger, J. L., Galliani, S., Sattler, T., Schindler, K., Pollefeys, M., Geiger, A.

In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (inproceedings)

Abstract
Motivated by the limitations of existing multi-view stereo benchmarks, we present a novel dataset for this task. Towards this goal, we recorded a variety of indoor and outdoor scenes using a high-precision laser scanner and captured both high-resolution DSLR imagery as well as synchronized low-resolution stereo videos with varying fields-of-view. To align the images with the laser scans, we propose a robust technique which minimizes photometric errors conditioned on the geometry. In contrast to previous datasets, our benchmark provides novel challenges and covers a diverse set of viewpoints and scene types, ranging from natural scenes to man-made indoor and outdoor environments. Furthermore, we provide data at significantly higher temporal and spatial resolution. Our benchmark is the first to cover the important use case of hand-held mobile devices while also providing high-resolution DSLR camera images. We make our datasets and an online evaluation server available at http://www.eth3d.net.

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pdf suppmat Project Page Project Page [BibTex]

pdf suppmat Project Page Project Page [BibTex]


Thumb xl camposeco2017cvpr
Toroidal Constraints for Two Point Localization Under High Outlier Ratios

Camposeco, F., Sattler, T., Cohen, A., Geiger, A., Pollefeys, M.

In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (inproceedings)

Abstract
Localizing a query image against a 3D model at large scale is a hard problem, since 2D-3D matches become more and more ambiguous as the model size increases. This creates a need for pose estimation strategies that can handle very low inlier ratios. In this paper, we draw new insights on the geometric information available from the 2D-3D matching process. As modern descriptors are not invariant against large variations in viewpoint, we are able to find the rays in space used to triangulate a given point that are closest to a query descriptor. It is well known that two correspondences constrain the camera to lie on the surface of a torus. Adding the knowledge of direction of triangulation, we are able to approximate the position of the camera from \emphtwo matches alone. We derive a geometric solver that can compute this position in under 1 microsecond. Using this solver, we propose a simple yet powerful outlier filter which scales quadratically in the number of matches. We validate the accuracy of our solver and demonstrate the usefulness of our method in real world settings.

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pdf suppmat Project Page Project Page [BibTex]

pdf suppmat Project Page pdf Project Page [BibTex]


Thumb xl cvpr2017 landpsace
Semantic Multi-view Stereo: Jointly Estimating Objects and Voxels

Ulusoy, A. O., Black, M. J., Geiger, A.

In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (inproceedings)

Abstract
Dense 3D reconstruction from RGB images is a highly ill-posed problem due to occlusions, textureless or reflective surfaces, as well as other challenges. We propose object-level shape priors to address these ambiguities. Towards this goal, we formulate a probabilistic model that integrates multi-view image evidence with 3D shape information from multiple objects. Inference in this model yields a dense 3D reconstruction of the scene as well as the existence and precise 3D pose of the objects in it. Our approach is able to recover fine details not captured in the input shapes while defaulting to the input models in occluded regions where image evidence is weak. Due to its probabilistic nature, the approach is able to cope with the approximate geometry of the 3D models as well as input shapes that are not present in the scene. We evaluate the approach quantitatively on several challenging indoor and outdoor datasets.

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YouTube pdf suppmat Project Page [BibTex]

YouTube pdf suppmat Project Page [BibTex]


Thumb xl publications toc
Dynamic analysis on hexapedal water-running robot with compliant joints

Kim, H., Liu, Y., Jeong, K., Sitti, M., Seo, T.

In 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pages: 250-251, June 2017 (inproceedings)

Abstract
The dynamic analysis has been considered as one of the important design methods to design robots. In this research, we derive dynamic equation of hexapedal water-running robot to design compliant joints. The compliant joints that connect three bodies will be used to improve mobility and stability of water-running motion's pitch behavior. We considered all of parts as rigid body including links of six Klann mechanisms and three main frames. And then, we derived dynamic equation by using the Lagrangian method with external force of the water. We are expecting that the dynamic analysis is going to be used to design parts of the water running robot.

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl imahe toc
Soiled adhesive pads shear clean by slipping: a robust self-cleaning mechanism in climbing beetles

Amador, G., Endlein, T., Sitti, M.

Journal of The Royal Society Interface, 14(131):20170134, The Royal Society, June 2017 (article)

Abstract
Animals using adhesive pads to climb smooth surfaces face the problem of keeping their pads clean and functional. Here, a self-cleaning mechanism is proposed whereby soiled feet would slip on the surface due to a lack of adhesion but shed particles in return. Our study offers an in situ quantification of self-cleaning performance in fibrillar adhesives, using the dock beetle as a model organism. After beetles soiled their pads by stepping into patches of spherical beads, we found that their gait was significantly affected. Specifically, soiled pads slipped 10 times further than clean pads, with more particles deposited for longer slips. Like previous studies, we found that particle size affected cleaning performance. Large (45 μm) beads were removed most effectively, followed by medium (10 μm) and small (1 μm). Consistent with our results from climbing beetles, force measurements on freshly severed legs revealed larger detachment forces of medium particles from adhesive pads compared to a flat surface, possibly due to interlocking between fibres. By contrast, dock leaves showed an overall larger affinity to the beads and thus reduced the need for cleaning. Self-cleaning through slippage provides a mechanism robust to particle size and may inspire solutions for artificial adhesives.

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Yield prediction in parallel homogeneous assembly

Ipparthi, D., Winslow, A., Sitti, M., Dorigo, M., Mastrangeli, M.

Soft Matter, 13, pages: 7595-7608, The Royal Society of Chemistry, June 2017 (article)

Abstract
We investigate the parallel assembly of two-dimensional{,} geometrically-closed modular target structures out of homogeneous sets of macroscopic components of varying anisotropy. The yield predicted by a chemical reaction network (CRN)-based model is quantitatively shown to reproduce experimental results over a large set of conditions. Scaling laws for parallel assembling systems are then derived from the model. By extending the validity of the CRN-based modelling{,} this work prompts analysis and solutions to the incompatible substructure problem.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Three‐dimensional patterning in biomedicine: Importance and applications in neuropharmacology

Ajay, V. S., Tanmay, G., Madu, B., Byung‐Wook, P., Thomas, E., Metin, S.

Journal of Biomedical Materials Research Part B: Applied Biomaterials, 106(3):1369-1382, June 2017 (article)

Abstract
Abstract Nature manufactures biological systems in three dimensions with precisely controlled spatiotemporal profiles on hierarchical length and time scales. In this article, we review 3D patterning of biological systems on synthetic platforms for neuropharmacological applications. We briefly describe 3D versus 2D chemical and topographical patterning methods and their limitations. Subsequently, an overview of introducing a third dimension in neuropharmacological research with delineation of chemical and topographical roles is presented. Finally, toward the end of this article, an explanation of how 3D patterning has played a pivotal role in relevant fields of neuropharmacology to understand neurophysiology during development, normal health, and disease conditions is described. The future prospects of organs‐on‐a‐‐like devices to mimic patterned blood–brain barrier in the context of neurotherapeutic discovery and development for the prioritization of lead candidates, membrane potential, and toxicity testing are also described. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 1369–1382, 2018.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl 07873311 toc
Tail-Assisted Mobility and Stability Enhancement in Yaw/Pitch Motions of a Water-Running Robot

Kim, H., Sitti, M., Seo, T.

IEEE/ASME Transactions on Mechatronics, 22(3):1207–1217, IEEE, June 2017 (article)

Abstract
Water-running robots have been developed inspired by a basilisk lizard, which demonstrates highly agile, stable, and energy-efficient locomotion on water surfaces. Current water-running robots are not as stable and agile as their biological counterparts. This study shows how the stability of a water-running robot in the pitch direction can be improved by using an active tail to enable increased propulsion. The mobility of the robot is also increased. To generate force in the pitch and yaw directions, a two-degrees-of-freedom tail is implemented with two circular plates to provide drag. We developed two types of dynamic models for pitch and yaw behavior, and the results are recursively calculated by considering the correlation between the models. The relationship between pitch motion and propulsion was analyzed by simulations. The steering behavior of the robot is also validated while considering the pitch behavior. Experiments were conducted to verify the simulation results.

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DOI [BibTex]

DOI [BibTex]


Thumb xl publications toc
Design and actuation of a magnetic millirobot under a constant unidirectional magnetic field

Erin, O., Giltinan, J., Tsai, L., Sitti, M.

In Proceedings 2017 IEEE International Conference on Robotics and Automation (ICRA), pages: 3404-3410, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

Abstract
Magnetic untethered millirobots, which are actuated and controlled by remote magnetic fields, have been proposed for medical applications due to their ability to safely pass through tissues at long ranges. For example, magnetic resonance imaging (MRI) systems with a 3-7 T constant unidirectional magnetic field and 3D gradient coils have been used to actuate magnetic robots. Such magnetically constrained systems place limits on the degrees of freedom that can be actuated for untethered devices. This paper presents a design and actuation methodology for a magnetic millirobot that exhibits both position and orientation control in 2D under a magnetic field, dominated by a constant unidirectional magnetic field as found in MRI systems. Placing a spherical permanent magnet, which is free to rotate inside the millirobot and located away from the center of mass, allows the generation of net forces and torques with applied 3D magnetic field gradients. We model this system in a 3D planar case and experimentally demonstrate open-loop control of both position and orientation by the applied 2D field gradients. The actuation performance is characterized across the most important design variables, and we experimentally demonstrate that the proposed approach is feasible.

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DOI [BibTex]

DOI [BibTex]


Thumb xl publications toc
Magnetically actuated soft capsule endoscope for fine-needle aspiration biopsy

Son, D., Dogan, M. D., Sitti, M.

In Proceedings 2017 IEEE International Conference on Robotics and Automation (ICRA), pages: 1132-1139, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

Abstract
This paper presents a magnetically actuated soft capsule endoscope for fine-needle aspiration biopsy (B-MASCE) in the upper gastrointestinal tract. A thin and hollow needle is attached to the capsule, which can penetrate deeply into tissues to obtain subsurface biopsy sample. The design utilizes a soft elastomer body as a compliant mechanism to guide the needle. An internal permanent magnet provides a means for both actuation and tracking. The capsule is designed to roll towards its target and then deploy the biopsy needle in a precise location selected as the target area. B-MASCE is controlled by multiple custom-designed electromagnets while its position and orientation are tracked by a magnetic sensor array. In in vitro trials, B-MASCE demonstrated rolling locomotion and biopsy of a swine tissue model positioned inside an anatomical human stomach model. It was confirmed after the experiment that a tissue sample was retained inside the needle.

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl image toc
Propulsion and Chemotaxis in Bacteria-Driven Microswimmers

Zhuang, J., Park, B., Sitti, M.

Advanced Science, 4(9):1700109, May 2017 (article)

Abstract
Despite the large body of experimental work recently on biohybrid microsystems, few studies have focused on theoretical modeling of such systems, which is essential to understand their underlying functioning mechanisms and hence design them optimally for a given application task. Therefore, this study focuses on developing a mathematical model to describe the 3D motion and chemotaxis of a type of widely studied biohybrid microswimmer, where spherical microbeads are driven by multiple attached bacteria. The model is developed based on the biophysical observations of the experimental system and is validated by comparing the model simulation with experimental 3D swimming trajectories and other motility characteristics, including mean squared displacement, speed, diffusivity, and turn angle. The chemotaxis modeling results of the microswimmers also agree well with the experiments, where a collective chemotactic behavior among multiple bacteria is observed. The simulation result implies that such collective chemotaxis behavior is due to a synchronized signaling pathway across the bacteria attached to the same microswimmer. Furthermore, the dependencies of the motility and chemotaxis of the microswimmers on certain system parameters, such as the chemoattractant concentration gradient, swimmer body size, and number of attached bacteria, toward an optimized design of such biohybrid system are studied. The optimized microswimmers would be used in targeted cargo, e.g., drug, imaging agent, gene, and RNA, transport and delivery inside the stagnant or low-velocity fluids of the human body as one of their potential biomedical applications.

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DOI Project Page [BibTex]


Thumb xl image toc
Dynamic and programmable self-assembly of micro-rafts at the air-water interface

Wang, W., Giltinan, J., Zakharchenko, S., Sitti, M.

Science Advances, 3(5):e1602522, American Association for the Advancement of Science, May 2017 (article)

Abstract
Dynamic self-assembled material systems constantly consume energy to maintain their spatiotemporal structures and functions. Programmable self-assembly translates information from individual parts to the collective whole. Combining dynamic and programmable self-assembly in a single platform opens up the possibilities to investigate both types of self-assembly simultaneously and to explore their synergy. This task is challenging because of the difficulty in finding suitable interactions that are both dissipative and programmable. We present a dynamic and programmable self-assembling material system consisting of spinning at the air-water interface circular magnetic micro-rafts of radius 50 μm and with cosinusoidal edge-height profiles. The cosinusoidal edge-height profiles not only create a net dissipative capillary repulsion that is sustained by continuous torque input but also enable directional assembly of micro-rafts. We uncover the layered arrangement of micro-rafts in the patterns formed by dynamic self-assembly and offer mechanistic insights through a physical model and geometric analysis. Furthermore, we demonstrate programmable self-assembly and show that a 4-fold rotational symmetry encoded in individual micro-rafts translates into 90° bending angles and square-based tiling in the assembled structures of micro-rafts. We anticipate that our dynamic and programmable material system will serve as a model system for studying nonequilibrium dynamics and statistical mechanics in the future

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl emthy 01
Presentation of functional groups on self-assembled supramolecular peptide nanofibers mimicking glycosaminoglycans for directed mesenchymal stem cell differentiation

Yasa, O., Uysal, O., Ekiz, M. S., Guler, M. O., Tekinay, A. B.

J. Mater. Chem. B, 5, pages: 4890-4900, The Royal Society of Chemistry, May 2017 (article)

Abstract
Organizational complexity and functional diversity of the extracellular matrix regulate cellular behaviors. The extracellular matrix is composed of various proteins in the form of proteoglycans{,} glycoproteins{,} and nanofibers whose types and combinations change depending on the tissue type. Proteoglycans{,} which are proteins that are covalently attached to glycosaminoglycans{,} contribute to the complexity of the microenvironment of the cells. The sulfation degree of the glycosaminoglycans is an important and distinct feature at specific developmental stages and tissue types. Peptide amphiphile nanofibers can mimic natural glycosaminoglycans and/or proteoglycans{,} and they form a synthetic nanofibrous microenvironment where cells can proliferate and differentiate towards different lineages. In this study{,} peptide nanofibers were used to provide varying degrees of sulfonation mimicking the natural glycosaminoglycans by forming a microenvironment for the survival and differentiation of stem cells. The effects of glucose{,} carboxylate{,} and sulfonate groups on the peptide nanofibers were investigated by considering the changes in the differentiation profiles of rat mesenchymal stem cells in the absence of any specific differentiation inducers in the culture medium. The results showed that a higher sulfonate-to-glucose ratio is associated with adipogenic differentiation and a higher carboxylate-to-glucose ratio is associated with osteochondrogenic differentiation of the rat mesenchymal stem cells. Overall{,} these results demonstrate that supramolecular peptide nanosystems can be used to understand the fine-tunings of the extracellular matrix such as sulfation profile on specific cell types.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl drotlef et al 2017 advanced materials
Bioinspired Composite Microfibers for Skin Adhesion and Signal Amplification of Wearable Sensors

Drotlef, D., Amjadi, M., Yunusa, M., Sitti, M.

Advanced Materials, 29(28):1701353, May 2017, Back Cover (article)

Abstract
A facile approach is proposed for superior conformation and adhesion of wearable sensors to dry and wet skin. Bioinspired skin-adhesive films are composed of elastomeric microfibers decorated with conformal and mushroom-shaped vinylsiloxane tips. Strong skin adhesion is achieved by crosslinking the viscous vinylsiloxane tips directly on the skin surface. Furthermore, composite microfibrillar adhesive films possess a high adhesion strength of 18 kPa due to the excellent shape adaptation of the vinylsiloxane tips to the multiscale roughness of the skin. As a utility of the skin-adhesive films in wearable-device applications, they are integrated with wearable strain sensors for respiratory and heart-rate monitoring. The signal-to-noise ratio of the strain sensor is significantly improved to 59.7 because of the considerable signal amplification of microfibrillar skin-adhesive films.

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DOI [BibTex]


Thumb xl mostaghaci et al 2017 advanced science
Bioadhesive Bacterial Microswimmers for Targeted Drug Delivery in the Urinary and Gastrointestinal Tracts

Mostaghaci, B., Yasa, O., Zhuang, J., Sitti, M.

Advanced Science, 4(6):1700058, May 2017 (article)

Abstract
Bacteria-driven biohybrid microswimmers (bacteriabots), which integrate motile bacterial cells and functional synthetic cargo parts (e.g., microparticles encapsulating drug), are recently studied for targeted drug delivery. However, adhesion of such bacteriabots to the tissues on the site of a disease (which can increase the drug delivery efficiency) is not studied yet. Here, this paper proposes an approach to attach bacteriabots to certain types of epithelial cells (expressing mannose on the membrane), based on the affinity between lectin molecules on the tip of bacterial type I pili and mannose molecules on the epithelial cells. It is shown that the bacteria can anchor their cargo particles to mannose-functionalized surfaces and mannose-expressing cells (ATCC HTB-9) using the lectin–mannose bond. The attachment mechanism is confirmed by comparing the adhesion of bacteriabots fabricated from bacterial strains with or without type I pili to mannose-covered surfaces and cells. The proposed bioadhesive motile system can be further improved by expressing more specific adhesion moieties on the membrane of the bacteria.

pi

DOI Project Page [BibTex]


Thumb xl image toc
Six Degree-of-Freedom Localization of Endoscopic Capsule Robots using Recurrent Neural Networks embedded into a Convolutional Neural Network

Turan, M., Abdullah, A., Jamiruddin, R., Araujo, H., Konukoglu, E., Sitti, M.

arXiv preprint arXiv:1705.06196, May 2017 (article)

Abstract
Since its development, ingestible wireless endoscopy is considered to be a painless diagnostic method to detect a number of diseases inside GI tract. Medical related engineering companies have made significant improvements in this technology in last decade; however, some major limitations still residue. Localization of the next generation steerable endoscopic capsule robot in six degreeof-freedom (DoF) and active motion control are some of these limitations. The significance of localization capability concerns with the doctors correct diagnosis of the disease area. This paper presents a very robust 6-DoF localization method based on supervised training of an architecture consisting of recurrent networks (RNN) embedded into a convolutional neural network (CNN) to make use of both just-in-moment information obtained by CNN and correlative information across frames obtained by RNN. To our knowledge, our idea of embedding RNNs into a CNN architecture is for the first time proposed in literature. The experimental results show that the proposed RNN-in-CNN architecture performs very well for endoscopic capsule robot localization in cases vignetting, reflection distortions, noise, sudden camera movements and lack of distinguishable features.

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DOI Project Page [BibTex]


Thumb xl publications toc
Controllable load sharing for soft adhesive interfaces on three-dimensional surfaces

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

Proceedings of the National Academy of Sciences, 114(22):E4344–E4353, National Acad Sciences, May 2017 (article)

Abstract
For adhering to three-dimensional (3D) surfaces or objects, current adhesion systems are limited by a fundamental trade-off between 3D surface conformability and high adhesion strength. This limitation arises from the need for a soft, mechanically compliant interface, which enables conformability to nonflat and irregularly shaped surfaces but significantly reduces the interfacial fracture strength. In this work, we overcome this trade-off with an adhesion-based soft-gripping system that exhibits enhanced fracture strength without sacrificing conformability to nonplanar 3D surfaces. Composed of a gecko-inspired elastomeric microfibrillar adhesive membrane supported by a pressure-controlled deformable gripper body, the proposed soft-gripping system controls the bonding strength by changing its internal pressure and exploiting the mechanics of interfacial equal load sharing. The soft adhesion system can use up to ∼26% of the maximum adhesion of the fibrillar membrane, which is 14× higher than the adhering membrane without load sharing. Our proposed load-sharing method suggests a paradigm for soft adhesion-based gripping and transfer-printing systems that achieves area scaling similar to that of a natural gecko footpad.

pi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl image toc
A Non-Rigid Map Fusion-Based RGB-Depth SLAM Method for Endoscopic Capsule Robots

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

arXiv preprint arXiv:1705.05444, May 2017 (article)

Abstract
In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is considered as a minimally invasive novel diagnostic technology to inspect the entire GI tract and to diagnose various diseases and pathologies. Since the development of this technology, medical device companies and many groups have made significant progress to turn such passive capsule endoscopes into robotic active capsule endoscopes to achieve almost all functions of current active flexible endoscopes. However, the use of robotic capsule endoscopy still has some challenges. One such challenge is the precise localization of such active devices in 3D world, which is essential for a precise three-dimensional (3D) mapping of the inner organ. A reliable 3D map of the explored inner organ could assist the doctors to make more intuitive and correct diagnosis. In this paper, we propose to our knowledge for the first time in literature a visual simultaneous localization and mapping (SLAM) method specifically developed for endoscopic capsule robots. The proposed RGB-Depth SLAM method is capable of capturing comprehensive dense globally consistent surfel-based maps of the inner organs explored by an endoscopic capsule robot in real time. This is achieved by using dense frame-to-model camera tracking and windowed surfelbased fusion coupled with frequent model refinement through non-rigid surface deformations.

pi

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Thumb xl hydrophobic toc
Hydrophobic pinning with copper nanowhiskers leads to bactericidal properties

Singh, A. V., Baylan, S., Park, B., Richter, G., Sitti, M.

PloS One, 12(4):e0175428, Public Library of Science, April 2017 (article)

Abstract
The considerable morbidity associated with hospitalized patients and clinics in developed countries due to biofilm formation on biomedical implants and surgical instruments is a heavy economic burden. An alternative to chemically treated surfaces for bactericidal activity started emerging from micro/nanoscale topographical cues in the last decade. Here, we demonstrate a putative antibacterial surface using copper nanowhiskers deposited by molecular beam epitaxy. Furthermore, the control of biological response is based on hydrophobic pinning of water droplets in the Wenzel regime, causing mechanical injury and cell death. Scanning electron microscopy images revealed the details of the surface morphology and non-contact mode laser scanning of the surface revealed the microtopography-associated quantitative parameters. Introducing the bacterial culture over nanowhiskers produces mechanical injury to cells, leading to a reduction in cell density over time due to local pinning of culture medium to whisker surfaces. Extended culture to 72 hours to observe biofilm formation revealed biofilm inhibition with scattered microcolonies and significantly reduced biovolume on nanowhiskers. Therefore, surfaces patterned with copper nanowhiskers can serve as potential antibiofilm surfaces. The topography-based antibacterial surfaces introduce a novel prospect in developing mechanoresponsive nanobiomaterials to reduce the risk of medical device biofilm-associated infections, contrary to chemical leaching of copper as a traditional bactericidal agent.

pi

link (url) [BibTex]

link (url) [BibTex]


Thumb xl image toc
Biohybrid microtube swimmers driven by single captured bacteria

Stanton, M. M., Park, B., Miguel-López, A., Ma, X., Sitti, M., Sánchez, S.

Small, 13(19), March 2017 (article)

Abstract
Bacteria biohybrids employ the motility and power of swimming bacteria to carry and maneuver microscale particles. They have the potential to perform microdrug and cargo delivery in vivo, but have been limited by poor design, reduced swimming capabilities, and impeded functionality. To address these challenge, motile Escherichia coli are captured inside electropolymerized microtubes, exhibiting the first report of a bacteria microswimmer that does not utilize a spherical particle chassis. Single bacterium becomes partially trapped within the tube and becomes a bioengine to push the microtube though biological media. Microtubes are modified with “smart” material properties for motion control, including a bacteria-attractant polydopamine inner layer, addition of magnetic components for external guidance, and a biochemical kill trigger to cease bacterium swimming on demand. Swimming dynamics of the bacteria biohybrid are quantified by comparing “length of protrusion” of bacteria from the microtubes with respect to changes in angular autocorrelation and swimmer mean squared displacement. The multifunctional microtubular swimmers present a new generation of biocompatible micromotors toward future microbiorobots and minimally invasive medical applications.

pi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Sticky Solution Provides Grip for the First Robotic Pollinator

Amador, G. J., Hu, D. L.

Chem, 2(2):162 - 164, Febuary 2017 (article)

Abstract
Bees, move over. A lily has been pollinated by a remote-controlled flying robot. The robot is hairy, just like a real bee, and sticks to pollen by virtue of an ionic liquid gel, whose fabrication is discussed by Svetlana Chechetka et al. in this issue of Chem.

pi

link (url) DOI [BibTex]


Thumb xl image toc
The use of clamping grips and friction pads by tree frogs for climbing curved surfaces

Endlein, T., Ji, A., Yuan, S., Hill, I., Wang, H., Barnes, W. J. P., Dai, Z., Sitti, M.

In Proc. R. Soc. B, 284(1849):20162867, Febuary 2017 (inproceedings)

Abstract
Most studies on the adhesive mechanisms of climbing animals have addressed attachment against flat surfaces, yet many animals can climb highly curved surfaces, like twigs and small branches. Here we investigated whether tree frogs use a clamping grip by recording the ground reaction forces on a cylindrical object with either a smooth or anti-adhesive, rough surface. Furthermore, we measured the contact area of fore and hindlimbs against differently sized transparent cylinders and the forces of individual pads and subarticular tubercles in restrained animals. Our study revealed that frogs use friction and normal forces of roughly a similar magnitude for holding on to cylindrical objects. When challenged with climbing a non-adhesive surface, the compressive forces between opposite legs nearly doubled, indicating a stronger clamping grip. In contrast to climbing flat surfaces, frogs increased the contact area on all limbs by engaging not just adhesive pads but also subarticular tubercles on curved surfaces. Our force measurements showed that tubercles can withstand larger shear stresses than pads. SEM images of tubercles revealed a similar structure to that of toe pads including the presence of nanopillars, though channels surrounding epithelial cells were less pronounced. The tubercles' smaller size, proximal location on the toes and shallow cells make them probably less prone to buckling and thus ideal for gripping curved surfaces.

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DOI [BibTex]

DOI [BibTex]


Thumb xl image toc
Rubbing Against Blood Clots Using Helical Robots: Modeling and In Vitro Experimental Validation

Khalil, I. S., Tabak, A. F., Sadek, K., Mahdy, D., Hamdi, N., Sitti, M.

IEEE Robotics and Automation Letters, 2(2):927-934, IEEE, January 2017 (article)

Abstract
The risk of side effects from thrombolytic agents can be minimized by using smaller doses, assisted by mechanical rubbing against blood clots using helical robots. Quantifying this observation, we study the influence of rubbing against clots on their removal rate in vitro. First, we present a hydrodynamic model of the helical robot based on the resistive-force theory to investigate the rubbing behavior of the clots using robot driven by two rotating dipole fields. Second, we experimentally evaluate the influence of the rubbing on the removal rate of the blood clots. Not only do we find that the removal rate of mechanical rubbing (-0.56 ± 0.27 mm3 /min) is approximately three times greater than the dissolution rate of chemical lysis using streptokinase (-0.17 ± 0.032 mm3/min), but we also show that this removal rate can be controlled via the rubbing speed of the robot.

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DOI [BibTex]

DOI [BibTex]


no image
Nanoscale topographical control of capillary assembly of nanoparticles

Flauraud, V., Mastrangeli, M., Bernasconi, G., Butet, J., Alexander, D., Shahrabi, E., Martin, O., Brugger, J.

Scientific Reports, Nature Nanotechnology, 12, pages: 73-80, January 2017 (article)

Abstract
Predetermined and selective placement of nanoparticles onto large-area substrates with nanometre-scale precision is essential to harness the unique properties of nanoparticle assemblies, in particular for functional optical and electro-optical nanodevices. Unfortunately, such high spatial organization is currently beyond the reach of top-down nanofabrication techniques alone. Here, we demonstrate that topographic features comprising lithographed funnelled traps and auxiliary sidewalls on a solid substrate can deterministically direct the capillary assembly of Au nanorods to attain simultaneous control of position, orientation and interparticle distance at the nanometre level. We report up to 100% assembly yield over centimetre-scale substrates. We achieve this by optimizing the three sequential stages of capillary nanoparticle assembly: insertion of nanorods into the traps, resilience against the receding suspension front and drying of the residual solvent. Finally, using electron energy-loss spectroscopy we characterize the spectral response and near-field properties of spatially programmable Au nanorod dimers, highlighting the opportunities for precise tunability of the plasmonic modes in larger assemblies.

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DOI [BibTex]

DOI [BibTex]