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2016


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Soft continuous microrobots with multiple intrinsic degrees of freedom

Palagi, S., Mark, A. G., Melde, K., Zeng, H., Parmeggiani, C., Martella, D., Wiersma, D. S., Fischer, P.

In 2016 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), pages: 1-5, July 2016 (inproceedings)

Abstract
One of the main challenges in the development of microrobots, i.e. robots at the sub-millimeter scale, is the difficulty of adopting traditional solutions for power, control and, especially, actuation. As a result, most current microrobots are directly manipulated by external fields, and possess only a few passive degrees of freedom (DOFs). We have reported a strategy that enables embodiment, remote powering and control of a large number of DOFs in mobile soft microrobots. These consist of photo-responsive materials, such that the actuation of their soft continuous body can be selectively and dynamically controlled by structured light fields. Here we use finite-element modelling to evaluate the effective number of DOFs that are addressable in our microrobots. We also demonstrate that by this flexible approach different actuation patterns can be obtained, and thus different locomotion performances can be achieved within the very same microrobot. The reported results confirm the versatility of the proposed approach, which allows for easy application-specific optimization and online reconfiguration of the microrobot's behavior. Such versatility will enable advanced applications of robotics and automation at the micro scale.

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DOI [BibTex]

2016


DOI [BibTex]


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Wireless actuator based on ultrasonic bubble streaming

Qiu, T., Palagi, S., Mark, A. G., Melde, K., Fischer, P.

In 2016 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), pages: 1-5, July 2016 (inproceedings)

Abstract
Miniaturized actuators are a key element for the manipulation and automation at small scales. Here, we propose a new miniaturized actuator, which consists of an array of micro gas bubbles immersed in a fluid. Under ultrasonic excitation, the oscillation of micro gas bubbles results in acoustic streaming and provides a propulsive force that drives the actuator. The actuator was fabricated by lithography and fluidic streaming was observed under ultrasound excitation. Theoretical modelling and numerical simulations were carried out to show that lowing the surface tension results in a larger amplitude of the bubble oscillation, and thus leads to a higher propulsive force. Experimental results also demonstrate that the propulsive force increases 3.5 times when the surface tension is lowered by adding a surfactant. An actuator with a 4×4 mm 2 surface area provides a driving force of about 0.46 mN, suggesting that it is possible to be used as a wireless actuator for small-scale robots and medical instruments.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Patches, Planes and Probabilities: A Non-local Prior for Volumetric 3D Reconstruction

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

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

Abstract
In this paper, we propose a non-local structured prior for volumetric multi-view 3D reconstruction. Towards this goal, we present a novel Markov random field model based on ray potentials in which assumptions about large 3D surface patches such as planarity or Manhattan world constraints can be efficiently encoded as probabilistic priors. We further derive an inference algorithm that reasons jointly about voxels, pixels and image segments, and estimates marginal distributions of appearance, occupancy, depth, normals and planarity. Key to tractable inference is a novel hybrid representation that spans both voxel and pixel space and that integrates non-local information from 2D image segmentations in a principled way. We compare our non-local prior to commonly employed local smoothness assumptions and a variety of state-of-the-art volumetric reconstruction baselines on challenging outdoor scenes with textureless and reflective surfaces. Our experiments indicate that regularizing over larger distances has the potential to resolve ambiguities where local regularizers fail.

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YouTube pdf poster suppmat Project Page [BibTex]

YouTube pdf poster suppmat Project Page [BibTex]


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Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer

Xie, J., Kiefel, M., Sun, M., Geiger, A.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

Abstract
Semantic annotations are vital for training models for object recognition, semantic segmentation or scene understanding. Unfortunately, pixelwise annotation of images at very large scale is labor-intensive and only little labeled data is available, particularly at instance level and for street scenes. In this paper, we propose to tackle this problem by lifting the semantic instance labeling task from 2D into 3D. Given reconstructions from stereo or laser data, we annotate static 3D scene elements with rough bounding primitives and develop a probabilistic model which transfers this information into the image domain. We leverage our method to obtain 2D labels for a novel suburban video dataset which we have collected, resulting in 400k semantic and instance image annotations. A comparison of our method to state-of-the-art label transfer baselines reveals that 3D information enables more efficient annotation while at the same time resulting in improved accuracy and time-coherent labels.

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pdf suppmat Project Page Project Page [BibTex]

pdf suppmat Project Page Project Page [BibTex]


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Auxetic Metamaterial Simplifies Soft Robot Design

Mark, A. G., Palagi, S., Qiu, T., Fischer, P.

In 2016 IEEE Int. Conf. on Robotics and Automation (ICRA), pages: 4951-4956, May 2016 (inproceedings)

Abstract
Soft materials are being adopted in robotics in order to facilitate biomedical applications and in order to achieve simpler and more capable robots. One route to simplification is to design the robot's body using `smart materials' that carry the burden of control and actuation. Metamaterials enable just such rational design of the material properties. Here we present a soft robot that exploits mechanical metamaterials for the intrinsic synchronization of two passive clutches which contact its travel surface. Doing so allows it to move through an enclosed passage with an inchworm motion propelled by a single actuator. Our soft robot consists of two 3D-printed metamaterials that implement auxetic and normal elastic properties. The design, fabrication and characterization of the metamaterials are described. In addition, a working soft robot is presented. Since the synchronization mechanism is a feature of the robot's material body, we believe that the proposed design will enable compliant and robust implementations that scale well with miniaturization.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Towards Photo-Induced Swimming: Actuation of Liquid Crystalline Elastomer in Water

cerretti, G., Martella, D., Zeng, H., Parmeggiani, C., Palagi, S., Mark, A. G., Melde, K., Qiu, T., Fischer, P., Wiersma, D.

In Proc. of SPIE 9738, pages: Laser 3D Manufacturing III, 97380T, April 2016 (inproceedings)

Abstract
Liquid Crystalline Elastomers (LCEs) are very promising smart materials that can be made sensitive to different external stimuli, such as heat, pH, humidity and light, by changing their chemical composition. In this paper we report the implementation of a nematically aligned LCE actuator able to undergo large light-induced deformations. We prove that this property is still present even when the actuator is submerged in fresh water. Thanks to the presence of azo-dye moieties, capable of going through a reversible trans-cis photo-isomerization, and by applying light with two different wavelengths we managed to control the bending of such actuator in the liquid environment. The reported results represent the first step towards swimming microdevices powered by light.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Deep Discrete Flow

Güney, F., Geiger, A.

Asian Conference on Computer Vision (ACCV), 2016 (conference) Accepted

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pdf suppmat Project Page [BibTex]

pdf suppmat Project Page [BibTex]

2015


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Exploiting Object Similarity in 3D Reconstruction

Zhou, C., Güney, F., Wang, Y., Geiger, A.

In International Conference on Computer Vision (ICCV), December 2015 (inproceedings)

Abstract
Despite recent progress, reconstructing outdoor scenes in 3D from movable platforms remains a highly difficult endeavor. Challenges include low frame rates, occlusions, large distortions and difficult lighting conditions. In this paper, we leverage the fact that the larger the reconstructed area, the more likely objects of similar type and shape will occur in the scene. This is particularly true for outdoor scenes where buildings and vehicles often suffer from missing texture or reflections, but share similarity in 3D shape. We take advantage of this shape similarity by locating objects using detectors and jointly reconstructing them while learning a volumetric model of their shape. This allows us to reduce noise while completing missing surfaces as objects of similar shape benefit from all observations for the respective category. We evaluate our approach with respect to LIDAR ground truth on a novel challenging suburban dataset and show its advantages over the state-of-the-art.

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pdf suppmat [BibTex]

2015


pdf suppmat [BibTex]


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FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation

Lenz, P., Geiger, A., Urtasun, R.

In International Conference on Computer Vision (ICCV), International Conference on Computer Vision (ICCV), December 2015 (inproceedings)

Abstract
One of the most popular approaches to multi-target tracking is tracking-by-detection. Current min-cost flow algorithms which solve the data association problem optimally have three main drawbacks: they are computationally expensive, they assume that the whole video is given as a batch, and they scale badly in memory and computation with the length of the video sequence. In this paper, we address each of these issues, resulting in a computationally and memory-bounded solution. First, we introduce a dynamic version of the successive shortest-path algorithm which solves the data association problem optimally while reusing computation, resulting in faster inference than standard solvers. Second, we address the optimal solution to the data association problem when dealing with an incoming stream of data (i.e., online setting). Finally, we present our main contribution which is an approximate online solution with bounded memory and computation which is capable of handling videos of arbitrary length while performing tracking in real time. We demonstrate the effectiveness of our algorithms on the KITTI and PETS2009 benchmarks and show state-of-the-art performance, while being significantly faster than existing solvers.

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pdf suppmat video project [BibTex]

pdf suppmat video project [BibTex]


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Towards Probabilistic Volumetric Reconstruction using Ray Potentials

(Best Paper Award)

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

In 3D Vision (3DV), 2015 3rd International Conference on, pages: 10-18, Lyon, October 2015 (inproceedings)

Abstract
This paper presents a novel probabilistic foundation for volumetric 3-d reconstruction. We formulate the problem as inference in a Markov random field, which accurately captures the dependencies between the occupancy and appearance of each voxel, given all input images. Our main contribution is an approximate highly parallelized discrete-continuous inference algorithm to compute the marginal distributions of each voxel's occupancy and appearance. In contrast to the MAP solution, marginals encode the underlying uncertainty and ambiguity in the reconstruction. Moreover, the proposed algorithm allows for a Bayes optimal prediction with respect to a natural reconstruction loss. We compare our method to two state-of-the-art volumetric reconstruction algorithms on three challenging aerial datasets with LIDAR ground truth. Our experiments demonstrate that the proposed algorithm compares favorably in terms of reconstruction accuracy and the ability to expose reconstruction uncertainty.

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code YouTube pdf suppmat DOI Project Page [BibTex]

code YouTube pdf suppmat DOI Project Page [BibTex]


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3D-printed Soft Microrobot for Swimming in Biological Fluids

Qiu, T., Palagi, S., Fischer, P.

In Conf. Proc. IEEE Eng. Med. Biol. Soc., pages: 4922-4925, August 2015 (inproceedings)

Abstract
Microscopic artificial swimmers hold the potential to enable novel non-invasive medical procedures. In order to ease their translation towards real biomedical applications, simpler designs as well as cheaper yet more reliable materials and fabrication processes should be adopted, provided that the functionality of the microrobots can be kept. A simple single-hinge design could already enable microswimming in non-Newtonian fluids, which most bodily fluids are. Here, we address the fabrication of such single-hinge microrobots with a 3D-printed soft material. Firstly, a finite element model is developed to investigate the deformability of the 3D-printed microstructure under typical values of the actuating magnetic fields. Then the microstructures are fabricated by direct 3D-printing of a soft material and their swimming performances are evaluated. The speeds achieved with the 3D-printed microrobots are comparable to those obtained in previous work with complex fabrication procedures, thus showing great promise for 3D-printed microrobots to be operated in biological fluids.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Displets: Resolving Stereo Ambiguities using Object Knowledge

Güney, F., Geiger, A.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2015, pages: 4165-4175, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2015 (inproceedings)

Abstract
Stereo techniques have witnessed tremendous progress over the last decades, yet some aspects of the problem still remain challenging today. Striking examples are reflecting and textureless surfaces which cannot easily be recovered using traditional local regularizers. In this paper, we therefore propose to regularize over larger distances using object-category specific disparity proposals (displets) which we sample using inverse graphics techniques based on a sparse disparity estimate and a semantic segmentation of the image. The proposed displets encode the fact that objects of certain categories are not arbitrarily shaped but typically exhibit regular structures. We integrate them as non-local regularizer for the challenging object class 'car' into a superpixel based CRF framework and demonstrate its benefits on the KITTI stereo evaluation.

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pdf abstract suppmat [BibTex]

pdf abstract suppmat [BibTex]


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Object Scene Flow for Autonomous Vehicles

Menze, M., Geiger, A.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2015, pages: 3061-3070, IEEE, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2015 (inproceedings)

Abstract
This paper proposes a novel model and dataset for 3D scene flow estimation with an application to autonomous driving. Taking advantage of the fact that outdoor scenes often decompose into a small number of independently moving objects, we represent each element in the scene by its rigid motion parameters and each superpixel by a 3D plane as well as an index to the corresponding object. This minimal representation increases robustness and leads to a discrete-continuous CRF where the data term decomposes into pairwise potentials between superpixels and objects. Moreover, our model intrinsically segments the scene into its constituting dynamic components. We demonstrate the performance of our model on existing benchmarks as well as a novel realistic dataset with scene flow ground truth. We obtain this dataset by annotating 400 dynamic scenes from the KITTI raw data collection using detailed 3D CAD models for all vehicles in motion. Our experiments also reveal novel challenges which can't be handled by existing methods.

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pdf abstract suppmat DOI [BibTex]

pdf abstract suppmat DOI [BibTex]


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Joint 3D Object and Layout Inference from a single RGB-D Image

(Best Paper Award)

Geiger, A., Wang, C.

In German Conference on Pattern Recognition (GCPR), 9358, pages: 183-195, Lecture Notes in Computer Science, Springer International Publishing, 2015 (inproceedings)

Abstract
Inferring 3D objects and the layout of indoor scenes from a single RGB-D image captured with a Kinect camera is a challenging task. Towards this goal, we propose a high-order graphical model and jointly reason about the layout, objects and superpixels in the image. In contrast to existing holistic approaches, our model leverages detailed 3D geometry using inverse graphics and explicitly enforces occlusion and visibility constraints for respecting scene properties and projective geometry. We cast the task as MAP inference in a factor graph and solve it efficiently using message passing. We evaluate our method with respect to several baselines on the challenging NYUv2 indoor dataset using 21 object categories. Our experiments demonstrate that the proposed method is able to infer scenes with a large degree of clutter and occlusions.

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pdf suppmat video project DOI [BibTex]

pdf suppmat video project DOI [BibTex]


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Discrete Optimization for Optical Flow

Menze, M., Heipke, C., Geiger, A.

In German Conference on Pattern Recognition (GCPR), 9358, pages: 16-28, Springer International Publishing, 2015 (inproceedings)

Abstract
We propose to look at large-displacement optical flow from a discrete point of view. Motivated by the observation that sub-pixel accuracy is easily obtained given pixel-accurate optical flow, we conjecture that computing the integral part is the hardest piece of the problem. Consequently, we formulate optical flow estimation as a discrete inference problem in a conditional random field, followed by sub-pixel refinement. Naive discretization of the 2D flow space, however, is intractable due to the resulting size of the label set. In this paper, we therefore investigate three different strategies, each able to reduce computation and memory demands by several orders of magnitude. Their combination allows us to estimate large-displacement optical flow both accurately and efficiently and demonstrates the potential of discrete optimization for optical flow. We obtain state-of-the-art performance on MPI Sintel and KITTI.

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pdf suppmat project DOI [BibTex]

pdf suppmat project DOI [BibTex]


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Joint 3D Estimation of Vehicles and Scene Flow

Menze, M., Heipke, C., Geiger, A.

In Proc. of the ISPRS Workshop on Image Sequence Analysis (ISA), 2015 (inproceedings)

Abstract
Three-dimensional reconstruction of dynamic scenes is an important prerequisite for applications like mobile robotics or autonomous driving. While much progress has been made in recent years, imaging conditions in natural outdoor environments are still very challenging for current reconstruction and recognition methods. In this paper, we propose a novel unified approach which reasons jointly about 3D scene flow as well as the pose, shape and motion of vehicles in the scene. Towards this goal, we incorporate a deformable CAD model into a slanted-plane conditional random field for scene flow estimation and enforce shape consistency between the rendered 3D models and the parameters of all superpixels in the image. The association of superpixels to objects is established by an index variable which implicitly enables model selection. We evaluate our approach on the challenging KITTI scene flow dataset in terms of object and scene flow estimation. Our results provide a prove of concept and demonstrate the usefulness of our method.

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PDF [BibTex]

PDF [BibTex]


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Combined FORC and x-ray microscopy study of magnetisation reversal in antidot lattices

Gräfe, J., Haering, F., Stahl, C., Weigand, M., Skripnik, M., Nowak, U., Ziemann, P., Wiedwald, U., Schütz, G., Goering, E.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


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Local control of domain wall dynamics in ferromagnetic rings

Richter, K., Mawass, M., Krone, A., Krüger, B., Weigand, M., Stoll, H., Schütz, G., Kläui, M.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Ultrafast demagnetization after laser pulse irradiation in Ni: Ab-initio electron-phonon scattering and phase space calculations

Illg, C., Haag, M., Fähnle, M.

In Ultrafast Magnetism I. Proceedings of the International Conference UMC 2013, 159, pages: 131-133, Springer Proceedings in Physics, Springer, Strasbourg, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Automotive domain wall propagation in ferromagnetic rings

Richter, K., Mawass, M., Krone, A., Krüger, B., Weigand, M., Schütz, G., Stoll, H., Kläui, M.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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The third dimension: Vortex core reversal by interaction with \textquotesingleflexure modes’

Noske, M., Stoll, H., Fähnle, M., Weigand, M., Dieterle, G., Förster, J., Gangwar, A., Slavin, A., Back, C. H., Schütz, G.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Skyrmions at room temperature in magnetic multilayers

Moreau-Luchaire, C., Reyren, N., Moutafis, C., Sampaio, J., Van Horne, N., Vaz, C. A., Warnicke, P., Garcia, K., Weigand, M., Bouzehouane, K., Deranlot, C., George, J., Raabe, J., Cros, V., Fert, A.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]

2007


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Geometric Image Synthesis

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

(conference)

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Project Page [BibTex]


Project Page [BibTex]