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2018


Softness, Warmth, and Responsiveness Improve Robot Hugs
Softness, Warmth, and Responsiveness Improve Robot Hugs

Block, A. E., Kuchenbecker, K. J.

International Journal of Social Robotics, 11(1):49-64, October 2018 (article)

Abstract
Hugs are one of the first forms of contact and affection humans experience. Due to their prevalence and health benefits, roboticists are naturally interested in having robots one day hug humans as seamlessly as humans hug other humans. This project's purpose is to evaluate human responses to different robot physical characteristics and hugging behaviors. Specifically, we aim to test the hypothesis that a soft, warm, touch-sensitive PR2 humanoid robot can provide humans with satisfying hugs by matching both their hugging pressure and their hugging duration. Thirty relatively young and rather technical participants experienced and evaluated twelve hugs with the robot, divided into three randomly ordered trials that focused on physical robot characteristics (single factor, three levels) and nine randomly ordered trials with low, medium, and high hug pressure and duration (two factors, three levels each). Analysis of the results showed that people significantly prefer soft, warm hugs over hard, cold hugs. Furthermore, users prefer hugs that physically squeeze them and release immediately when they are ready for the hug to end. Taking part in the experiment also significantly increased positive user opinions of robots and robot use.

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link (url) DOI Project Page [BibTex]

2018


link (url) DOI Project Page [BibTex]


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Complexity, Rate, and Scale in Sliding Friction Dynamics Between a Finger and Textured Surface

Khojasteh, B., Janko, M., Visell, Y.

Nature Scientific Reports, 8(13710), September 2018 (article)

Abstract
Sliding friction between the skin and a touched surface is highly complex, but lies at the heart of our ability to discriminate surface texture through touch. Prior research has elucidated neural mechanisms of tactile texture perception, but our understanding of the nonlinear dynamics of frictional sliding between the finger and textured surfaces, with which the neural signals that encode texture originate, is incomplete. To address this, we compared measurements from human fingertips sliding against textured counter surfaces with predictions of numerical simulations of a model finger that resembled a real finger, with similar geometry, tissue heterogeneity, hyperelasticity, and interfacial adhesion. Modeled and measured forces exhibited similar complex, nonlinear sliding friction dynamics, force fluctuations, and prominent regularities related to the surface geometry. We comparatively analysed measured and simulated forces patterns in matched conditions using linear and nonlinear methods, including recurrence analysis. The model had greatest predictive power for faster sliding and for surface textures with length scales greater than about one millimeter. This could be attributed to the the tendency of sliding at slower speeds, or on finer surfaces, to complexly engage fine features of skin or surface, such as fingerprints or surface asperities. The results elucidate the dynamical forces felt during tactile exploration and highlight the challenges involved in the biological perception of surface texture via touch.

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DOI [BibTex]

DOI [BibTex]


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Design of curved composite panels for optimal dynamic response using lamination parameters

Serhat, G., Basdogan, I.

Composites Part B: Engineering, 147, pages: 135–146, August 2018 (article)

Abstract
In this paper, dynamic response of composite panels is investigated using lamination parameters as design variables. Finite element analyses are performed to observe the individual and combined effects of different panel aspect ratios, curvatures and boundary conditions on the dynamic responses. Fundamental frequency contours for curved panels are obtained in lamination parameters domain and optimal points yielding maximum values are found. Subsequently, forced dynamic analyses are carried out to calculate equivalent radiated power (ERP) for the panels under harmonic pressure excitation. ERP contours at the maximum fundamental frequency are presented. Optimal lamination parameters providing minimum ERP are determined for different excitation frequencies and their effective frequency bands are shown. The relationship between the designs optimized for maximum fundamental frequency and minimum ERP responses is investigated to study the effectiveness of the frequency maximization technique. The results demonstrate the potential of using lamination parameters technique in the design of curved composite panels for optimal dynamic response and provide valuable insight on the effect of various design parameters.

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DOI [BibTex]

DOI [BibTex]


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A Robust Soft Lens for Tunable Camera Application Using Dielectric Elastomer Actuators

Nam, S., Yun, S., Yoon, J. W., Park, S., Park, S. K., Mun, S., Park, B., Kyung, K.

Soft robotics, Mary Ann Liebert, Inc., August 2018 (article)

Abstract
Developing tunable lenses, an expansion-based mechanism for dynamic focus adjustment can provide a larger focal length tuning range than a contraction-based mechanism. Here, we develop an expansion-tunable soft lens module using a disk-type dielectric elastomer actuator (DEA) that creates axially symmetric pulling forces on a soft lens. Adopted from a biological accommodation mechanism in human eyes, a soft lens at the annular center of a disk-type DEA pair is efficiently stretched to change the focal length in a highly reliable manner. A soft lens with a diameter of 3mm shows a 65.7% change in the focal length (14.3–23.7mm) under a dynamic driving voltage signal control. We confirm a quadratic relation between lens expansion and focal length that leads to large focal length tunability obtainable in the proposed approach. The fabricated tunable lens module can be used for soft, lightweight, and compact vision components in robots, drones, vehicles, and so on.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Task-Driven PCA-Based Design Optimization of Wearable Cutaneous Devices

Pacchierotti, C., Young, E. M., Kuchenbecker, K. J.

IEEE Robotics and Automation Letters, 3(3):2214-2221, July 2018, Presented at ICRA 2018 (article)

Abstract
Small size and low weight are critical requirements for wearable and portable haptic interfaces, making it essential to work toward the optimization of their sensing and actuation systems. This paper presents a new approach for task-driven design optimization of fingertip cutaneous haptic devices. Given one (or more) target tactile interactions to render and a cutaneous device to optimize, we evaluate the minimum number and best configuration of the device’s actuators to minimize the estimated haptic rendering error. First, we calculate the motion needed for the original cutaneous device to render the considered target interaction. Then, we run a principal component analysis (PCA) to search for possible couplings between the original motor inputs, looking also for the best way to reconfigure them. If some couplings exist, we can re-design our cutaneous device with fewer motors, optimally configured to render the target tactile sensation. The proposed approach is quite general and can be applied to different tactile sensors and cutaneous devices. We validated it using a BioTac tactile sensor and custom plate-based 3-DoF and 6-DoF fingertip cutaneous devices, considering six representative target tactile interactions. The algorithm was able to find couplings between each device’s motor inputs, proving it to be a viable approach to optimize the design of wearable and portable cutaneous devices. Finally, we present two examples of optimized designs for our 3-DoF fingertip cutaneous device.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn {IMU}s
Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn IMUs

Fitter, N. T., Kuchenbecker, K. J.

Frontiers in Robotics and Artificial Intelligence, 5(85), July 2018 (article)

Abstract
Colleagues often shake hands in greeting, friends connect through high fives, and children around the world rejoice in hand-clapping games. As robots become more common in everyday human life, they will have the opportunity to join in these social-physical interactions, but few current robots are intended to touch people in friendly ways. This article describes how we enabled a Baxter Research Robot to both teach and learn bimanual hand-clapping games with a human partner. Our system monitors the user's motions via a pair of inertial measurement units (IMUs) worn on the wrists. We recorded a labeled library of 10 common hand-clapping movements from 10 participants; this dataset was used to train an SVM classifier to automatically identify hand-clapping motions from previously unseen participants with a test-set classification accuracy of 97.0%. Baxter uses these sensors and this classifier to quickly identify the motions of its human gameplay partner, so that it can join in hand-clapping games. This system was evaluated by N = 24 naïve users in an experiment that involved learning sequences of eight motions from Baxter, teaching Baxter eight-motion game patterns, and completing a free interaction period. The motion classification accuracy in this less structured setting was 85.9%, primarily due to unexpected variations in motion timing. The quantitative task performance results and qualitative participant survey responses showed that learning games from Baxter was significantly easier than teaching games to Baxter, and that the teaching role caused users to consider more teamwork aspects of the gameplay. Over the course of the experiment, people felt more understood by Baxter and became more willing to follow the example of the robot. Users felt uniformly safe interacting with Baxter, and they expressed positive opinions of Baxter and reported fun interacting with the robot. Taken together, the results indicate that this robot achieved credible social-physical interaction with humans and that its ability to both lead and follow systematically changed the human partner's experience.

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DOI [BibTex]

DOI [BibTex]


Learning 3D Shape Completion under Weak Supervision
Learning 3D Shape Completion under Weak Supervision

Stutz, D., Geiger, A.

Arxiv, May 2018 (article)

Abstract
We address the problem of 3D shape completion from sparse and noisy point clouds, a fundamental problem in computer vision and robotics. Recent approaches are either data-driven or learning-based: Data-driven approaches rely on a shape model whose parameters are optimized to fit the observations; Learning-based approaches, in contrast, avoid the expensive optimization step by learning to directly predict complete shapes from incomplete observations in a fully-supervised setting. However, full supervision is often not available in practice. In this work, we propose a weakly-supervised learning-based approach to 3D shape completion which neither requires slow optimization nor direct supervision. While we also learn a shape prior on synthetic data, we amortize, i.e., learn, maximum likelihood fitting using deep neural networks resulting in efficient shape completion without sacrificing accuracy. On synthetic benchmarks based on ShapeNet and ModelNet as well as on real robotics data from KITTI and Kinect, we demonstrate that the proposed amortized maximum likelihood approach is able to compete with fully supervised baselines and outperforms data-driven approaches, while requiring less supervision and being significantly faster.

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PDF Project Page Project Page [BibTex]


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Automatically Rating Trainee Skill at a Pediatric Laparoscopic Suturing Task

Oquendo, Y. A., Riddle, E. W., Hiller, D., Blinman, T. A., Kuchenbecker, K. J.

Surgical Endoscopy, 32(4):1840-1857, April 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Electroelastic modeling of thin-laminated composite plates with surface-bonded piezo-patches using Rayleigh–Ritz method

Gozum, M. M., Aghakhani, A., Serhat, G., Basdogan, I.

Journal of Intelligent Material Systems and Structures, 29(10):2192–2205, March 2018 (article)

Abstract
Laminated composite panels are extensively used in various engineering applications. Piezoelectric transducers can be integrated into such composite structures for a variety of vibration control and energy harvesting applications. Analyzing the structural dynamics of such electromechanical systems requires precise modeling tools which properly consider the coupling between the piezoelectric elements and the laminates. Although previous analytical models in the literature cover vibration analysis of laminated composite plates with fully covered piezoelectric layers, they do not provide a formulation for modeling the piezoelectric patches that partially cover the plate surface. In this study, a methodology for vibration analysis of laminated composite plates with surface-bonded piezo-patches is developed. Rayleigh–Ritz method is used for solving the modal analysis and obtaining the frequency response functions. The developed model includes mass and stiffness contribution of the piezo-patches as well as the two-way electromechanical coupling effect. Moreover, an accelerated method is developed for reducing the computation time of the modal analysis solution. For validations, system-level finite element simulations are performed in ANSYS software. The results show that the developed analytical model can be utilized for accurate and efficient analysis and design of laminated composite plates with surface-bonded piezo-patches.

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DOI [BibTex]

DOI [BibTex]


Electro-Active Polymer Based Soft Tactile Interface for Wearable Devices
Electro-Active Polymer Based Soft Tactile Interface for Wearable Devices

Mun, S., Yun, S., Nam, S., Park, S. K., Park, S., Park, B. J., Lim, J. M., Kyung, K. U.

IEEE Transactions on Haptics, 11(1):15-21, Febuary 2018 (article)

Abstract
This paper reports soft actuator based tactile stimulation interfaces applicable to wearable devices. The soft actuator is prepared by multi-layered accumulation of thin electro-active polymer (EAP) films. The multi-layered actuator is designed to produce electrically-induced convex protrusive deformation, which can be dynamically programmable for wide range of tactile stimuli. The maximum vertical protrusion is 650 μm and the output force is up to 255 mN. The soft actuators are embedded into the fingertip part of a glove and front part of a forearm band, respectively. We have conducted two kinds of experiments with 15 subjects. Perceived magnitudes of actuator's protrusion and vibrotactile intensity were measured with frequency of 1 Hz and 191 Hz, respectively. Analysis of the user tests shows participants perceive variation of protrusion height at the finger pad and modulation of vibration intensity through the proposed soft actuator based tactile interface.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Robotic Motion Learning Framework to Promote Social Engagement
Robotic Motion Learning Framework to Promote Social Engagement

Burns, R., Jeon, M., Park, C. H.

Applied Sciences, 8(2):241, Febuary 2018, Special Issue "Social Robotics" (article)

Abstract
Imitation is a powerful component of communication between people, and it poses an important implication in improving the quality of interaction in the field of human–robot interaction (HRI). This paper discusses a novel framework designed to improve human–robot interaction through robotic imitation of a participant’s gestures. In our experiment, a humanoid robotic agent socializes with and plays games with a participant. For the experimental group, the robot additionally imitates one of the participant’s novel gestures during a play session. We hypothesize that the robot’s use of imitation will increase the participant’s openness towards engaging with the robot. Experimental results from a user study of 12 subjects show that post-imitation, experimental subjects displayed a more positive emotional state, had higher instances of mood contagion towards the robot, and interpreted the robot to have a higher level of autonomy than their control group counterparts did. These results point to an increased participant interest in engagement fueled by personalized imitation during interaction.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Active microrheology in corrugated channels

Puertas, A. M., Malgaretti, P., Pagonabarraga, I.

The Journal of Chemical Physics, 149(17), American Institute of Physics, Woodbury, N.Y., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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First-passage dynamics of linear stochastic interface models: weak-noise theory and influence of boundary conditions

Gross, M.

Journal of Statistical Mechanics: Theory and Experiment, 2018, Institute of Physics Publishing, Bristol, England, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Cu@TiO2 Janus microswimmers with a versatile motion mechanism

Wang, L. L., Popescu, M. N., Stavale, F., Ali, A., Gemming, T., Simmchen, J.

Soft Matter, 14(34):6969-6973, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Probing interface localization-delocalization transitions by colloids

Kondrat, S., Vasilyev, O., Dietrich, S.

Journal of Physics: Condensed Matter, 30(41), IOP Publishing, Bristol, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Medical imaging for the tracking of micromotors

Vilela, D., Coss\’\io, U., Parmar, J., Mart\’\inez-Villacorta, A. M., Gómez-Vallejo, V., Llop, J., Sánchez, S.

ACS Nano, 12(2):1220-1227, American Chemical Society, Washington, DC, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Noncontinuous Super-Diffusive Dynamics of a Light-Activated Nanobottle Motor

Xuan, M., Mestre, R., Gao, C., Zhou, C., He, Q., Sánchez, S.

Angewandte Chemie International Edition, 57(23):6838-6842, Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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On the origin of forward-backward multiplicity correlations in pp collisions at ultrarelativistic energies

Bravina, L., Bleibel, J., Zabrodin, E.

Physics Letters B, 787, pages: 146-152, North-Holland, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Autophoretic motion in three dimensions

Lisicki, M., Reigh, S., Lauga, E.

Soft Matter, 14(17):3304-3314, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Order-disorder transitions in lattice gases with annealed reactive constraints

Dudka, M., Bénichou, O., Oshanin, G.

Journal of Statistical Mechanics: Theory and Experiment, 2018, Institute of Physics Publishing, Bristol, England, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Bacterial Biohybrid Microswimmers

Bastos-Arrieta, J., Revilla-Guarinos, A., Uspal, W., Simmchen, J.

Frontiers in Robotics and AI, 5, Frontiers Media, Lausanne, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Fluctuational electrodynamics for nonlinear materials in and out of thermal equilibrium

Soo, H., Krüger, M.

Physical Review B, 97(4), American Physical Society, Woodbury, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Local pressure for confined systems

Malgaretti, P., Bier, M.

Physical Review E, 97(2), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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

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

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

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

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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

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

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

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Charge polarization, local electroneutrality breakdown and eddy formation due to electroosmosis in varying-section channels

Chinappi, M., Malgaretti, P.

Soft Matter, 14(45):9083-9087, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Critical Casimir interactions and percolation: The quantitative description of critical fluctuations

Vasilyev, O.

Physical Review E, 98(6), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Shear-density coupling for a compressible single-component yield-stress fluid

Gross, M., Varnik, F.

Soft Matter, 14(22):4577-4590, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Shape-dependent guidance of active Janus particles by chemically patterned surfaces

Uspal, W. E., Popescu, M. N., Tasinkevych, M., Dietrich, S.

New Journal of Physics, 20, IOP Publishing, Bristol, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Extrapolation to nonequilibrium from coarse-grained response theory

Basu, U., Helden, L., Krüger, M.

Physical Review Letters, 120(18), American Physical Society, Woodbury, N.Y., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Directed Flow of Micromotors through Alignment Interactions with Micropatterned Ratchets

Katuri, J., Caballero, D., Voituriez, R., Samitier, J., Sánchez, S.

ACS Nano, 12(7):7282-7291, American Chemical Society, Washington, DC, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Spontaneous symmetry breaking of charge-regulated surfaces

Majee, A., Bier, M., Podgornik, R.

Soft Matter, 14(6):985-991, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Electrostatic interaction between dissimilar colloids at fluid interfaces

Majee, A., Schmetzer, T., Bier, M.

Physical Review E, 97(4), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Wetting transition of a cylindrical cavity engraved on a hydrophobic surface

Kim, H., Ha, M. Y., Jang, J.

The Journal of Physical Chemistry C, 122(4):2122-2126, American Chemical Society, Washington, D.C., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Curvature corrections to the nonlocal interfacial model for short-ranged forces

Romero-Enrique, J.M., Squarcini, Alessio, Parry, A. O., Goldbart, P. M.

Physical Review E, 97(6), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Effective squirmer models for self-phoretic chemically active spherical colloids

Popescu, M. N., Uspal, W. E., Eskandari, Z., Tasinkevych, M., Dietrich, S.

The European Physical Journal E, 41(12), EDP Sciences; Società Italiana di Fisica; Springer, Les Ulis; Bologna; Heidelberg, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Two time scales for self and collective diffusion near the critical point in a simple patchy model for proteins with floating bonds

Bleibel, J., Habiger, M., Lütje, M., Hirschmann, F., Roosen-Runge, F., Seydel, T., Zhang, F., Schreiber, F., Oettel, M.

Soft Matter, 14(39):8006-8016, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Globulelike Conformation and Enhanced Diffusion of Active Polymers

Bianco, V., Locatelli, E., Malgaretti, P.

Physical Review Letters, 121(21), American Physical Society, Woodbury, N.Y., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Rheological behavior of colloidal suspension with long-range interactions

Arietaleaniz, S., Malgaretti, P., Pagonabarraga, I., Hidalgo, R. C.

Physical Review E, 98(4), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Solvent coarsening around colloids driven by temperature gradients

Roy, S., Dietrich, S., Maciolek, A.

Physical Review E, 97(4), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Cross-stream migration of active particles

Katuri, J., Uspal, W., Simmchen, J., López, A. M., Sanchez, S.

Science Advances, 4(1), AAAS, Washington, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Transient dynamics of electric double-layer capacitors: Exact expressions within the Debye-Falkenhagen approximation

Janssen, M., Bier, M.

Physical Review E, 97(5), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Coalescence preference and droplet size inequality during fluid phase segregation

Roy, S.

EPL, 121(3), EDP Science, Les-Ulis, 2018 (article)

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DOI [BibTex]


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Structure of interfaces at phase coexistence. Theory and numerics

Delfino, G., Selke, W., Squarcini, A.

Journal of Statistical Mechanics: Theory and Experiment, 2018, Institute of Physics Publishing, Bristol, England, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Power spectral density of a single Brownian trajectory: what one can and cannot learn from it

Krapf, D., Marinari, E., Metzler, Ralf, Oshanin, Gleb, Xu, Xinran, Squarcini, A.

New Journal of Physics, 20, IOP Publishing, Bristol, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Diffusiophoretically induced interactions between chemically active and inert particles

Reigh, Shang-Yik, Chuphal, P., Thakur, S., Kapral, R.

Soft Matter, 14(29):6043-6057, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Collective behavior of colloids due to critical Casimir interactions

Maciolek, A., Dietrich, S.

Reviews of Modern Physics, 90(4), American Physical Society, Minneapolis, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


Learning 3D Shape Completion under Weak Supervision
Learning 3D Shape Completion under Weak Supervision

Stutz, D., Geiger, A.

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

Abstract
We address the problem of 3D shape completion from sparse and noisy point clouds, a fundamental problem in computer vision and robotics. Recent approaches are either data-driven or learning-based: Data-driven approaches rely on a shape model whose parameters are optimized to fit the observations; Learning-based approaches, in contrast, avoid the expensive optimization step by learning to directly predict complete shapes from incomplete observations in a fully-supervised setting. However, full supervision is often not available in practice. In this work, we propose a weakly-supervised learning-based approach to 3D shape completion which neither requires slow optimization nor direct supervision. While we also learn a shape prior on synthetic data, we amortize, i.e., learn, maximum likelihood fitting using deep neural networks resulting in efficient shape completion without sacrificing accuracy. On synthetic benchmarks based on ShapeNet and ModelNet as well as on real robotics data from KITTI and Kinect, we demonstrate that the proposed amortized maximum likelihood approach is able to compete with a fully supervised baseline and outperforms the data-driven approach of Engelmann et al., while requiring less supervision and being significantly faster.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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Heat radiation and transfer in confinement

Asheichyk, K., Krüger, M.

Physical Review B, 98(19), American Physical Society, Woodbury, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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A ferronematic slab in external magnetic fields

Zarubin, G., Bier, M., Dietrich, S.

Soft Matter, 14(48):9806-9818, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]