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2020


Learning of sub-optimal gait controllers for magnetic walking soft millirobots
Learning of sub-optimal gait controllers for magnetic walking soft millirobots

Culha, U., Demir, S. O., Trimpe, S., Sitti, M.

In Proceedings of Robotics: Science and Systems, July 2020, Culha and Demir are equally contributing authors (inproceedings)

Abstract
Untethered small-scale soft robots have promising applications in minimally invasive surgery, targeted drug delivery, and bioengineering applications as they can access confined spaces in the human body. However, due to highly nonlinear soft continuum deformation kinematics, inherent stochastic variability during fabrication at the small scale, and lack of accurate models, the conventional control methods cannot be easily applied. Adaptivity of robot control is additionally crucial for medical operations, as operation environments show large variability, and robot materials may degrade or change over time,which would have deteriorating effects on the robot motion and task performance. Therefore, we propose using a probabilistic learning approach for millimeter-scale magnetic walking soft robots using Bayesian optimization (BO) and Gaussian processes (GPs). Our approach provides a data-efficient learning scheme to find controller parameters while optimizing the stride length performance of the walking soft millirobot robot within a small number of physical experiments. We demonstrate adaptation to fabrication variabilities in three different robots and to walking surfaces with different roughness. We also show an improvement in the learning performance by transferring the learning results of one robot to the others as prior information.

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link (url) DOI [BibTex]

2020


link (url) DOI [BibTex]


Learning to Dress 3D People in Generative Clothing
Learning to Dress 3D People in Generative Clothing

Ma, Q., Yang, J., Ranjan, A., Pujades, S., Pons-Moll, G., Tang, S., Black, M. J.

In Computer Vision and Pattern Recognition (CVPR), June 2020 (inproceedings)

Abstract
Three-dimensional human body models are widely used in the analysis of human pose and motion. Existing models, however, are learned from minimally-clothed 3D scans and thus do not generalize to the complexity of dressed people in common images and videos. Additionally, current models lack the expressive power needed to represent the complex non-linear geometry of pose-dependent clothing shape. To address this, we learn a generative 3D mesh model of clothed people from 3D scans with varying pose and clothing. Specifically, we train a conditional Mesh-VAE-GAN to learn the clothing deformation from the SMPL body model, making clothing an additional term on SMPL. Our model is conditioned on both pose and clothing type, giving the ability to draw samples of clothing to dress different body shapes in a variety of styles and poses. To preserve wrinkle detail, our Mesh-VAE-GAN extends patchwise discriminators to 3D meshes. Our model, named CAPE, represents global shape and fine local structure, effectively extending the SMPL body model to clothing. To our knowledge, this is the first generative model that directly dresses 3D human body meshes and generalizes to different poses.

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arxiv project page [BibTex]


{GENTEL : GENerating Training data Efficiently for Learning to segment medical images}
GENTEL : GENerating Training data Efficiently for Learning to segment medical images

Thakur, R. P., Rocamora, S. P., Goel, L., Pohmann, R., Machann, J., Black, M. J.

Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFAIP), June 2020 (conference)

Abstract
Accurately segmenting MRI images is crucial for many clinical applications. However, manually segmenting images with accurate pixel precision is a tedious and time consuming task. In this paper we present a simple, yet effective method to improve the efficiency of the image segmentation process. We propose to transform the image annotation task into a binary choice task. We start by using classical image processing algorithms with different parameter values to generate multiple, different segmentation masks for each input MRI image. Then, instead of segmenting the pixels of the images, the user only needs to decide whether a segmentation is acceptable or not. This method allows us to efficiently obtain high quality segmentations with minor human intervention. With the selected segmentations, we train a state-of-the-art neural network model. For the evaluation, we use a second MRI dataset (1.5T Dataset), acquired with a different protocol and containing annotations. We show that the trained network i) is able to automatically segment cases where none of the classical methods obtain a high quality result ; ii) generalizes to the second MRI dataset, which was acquired with a different protocol and was never seen at training time ; and iii) enables detection of miss-annotations in this second dataset. Quantitatively, the trained network obtains very good results: DICE score - mean 0.98, median 0.99- and Hausdorff distance (in pixels) - mean 4.7, median 2.0-.

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[BibTex]

[BibTex]


Generating 3D People in Scenes without People
Generating 3D People in Scenes without People

Zhang, Y., Hassan, M., Neumann, H., Black, M. J., Tang, S.

In Computer Vision and Pattern Recognition (CVPR), June 2020 (inproceedings)

Abstract
We present a fully automatic system that takes a 3D scene and generates plausible 3D human bodies that are posed naturally in that 3D scene. Given a 3D scene without people, humans can easily imagine how people could interact with the scene and the objects in it. However, this is a challenging task for a computer as solving it requires that (1) the generated human bodies to be semantically plausible within the 3D environment (e.g. people sitting on the sofa or cooking near the stove), and (2) the generated human-scene interaction to be physically feasible such that the human body and scene do not interpenetrate while, at the same time, body-scene contact supports physical interactions. To that end, we make use of the surface-based 3D human model SMPL-X. We first train a conditional variational autoencoder to predict semantically plausible 3D human poses conditioned on latent scene representations, then we further refine the generated 3D bodies using scene constraints to enforce feasible physical interaction. We show that our approach is able to synthesize realistic and expressive 3D human bodies that naturally interact with 3D environment. We perform extensive experiments demonstrating that our generative framework compares favorably with existing methods, both qualitatively and quantitatively. We believe that our scene-conditioned 3D human generation pipeline will be useful for numerous applications; e.g. to generate training data for human pose estimation, in video games and in VR/AR. Our project page for data and code can be seen at: \url{https://vlg.inf.ethz.ch/projects/PSI/}.

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Code PDF [BibTex]

Code PDF [BibTex]


SIMULTANEOUS CALIBRATION METHOD FOR MAGNETIC LOCALIZATION AND ACTUATION SYSTEMS
SIMULTANEOUS CALIBRATION METHOD FOR MAGNETIC LOCALIZATION AND ACTUATION SYSTEMS

Sitti, M., Son, D., Dong, X.

June 2020, US Patent App. 16/696,605 (misc)

Abstract
The invention relates to a method of simultaneously calibrating magnetic actuation and sensing systems for a workspace, wherein the actuation system comprises a plurality of magnetic actuators and the sensing system comprises a plurality of magnetic sensors, wherein all the measured data is fed into a calibration model, wherein the calibration model is based on a sensor measurement model and a magnetic actuation model, and wherein a solution of the model parameters is found via a numerical solver order to calibrate both the actuation and sensing systems at the same time.

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[BibTex]


Learning Physics-guided Face Relighting under Directional Light
Learning Physics-guided Face Relighting under Directional Light

Nestmeyer, T., Lalonde, J., Matthews, I., Lehrmann, A. M.

In Conference on Computer Vision and Pattern Recognition, IEEE/CVF, June 2020 (inproceedings) Accepted

Abstract
Relighting is an essential step in realistically transferring objects from a captured image into another environment. For example, authentic telepresence in Augmented Reality requires faces to be displayed and relit consistent with the observer's scene lighting. We investigate end-to-end deep learning architectures that both de-light and relight an image of a human face. Our model decomposes the input image into intrinsic components according to a diffuse physics-based image formation model. We enable non-diffuse effects including cast shadows and specular highlights by predicting a residual correction to the diffuse render. To train and evaluate our model, we collected a portrait database of 21 subjects with various expressions and poses. Each sample is captured in a controlled light stage setup with 32 individual light sources. Our method creates precise and believable relighting results and generalizes to complex illumination conditions and challenging poses, including when the subject is not looking straight at the camera.

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Paper [BibTex]

Paper [BibTex]


{VIBE}: Video Inference for Human Body Pose and Shape Estimation
VIBE: Video Inference for Human Body Pose and Shape Estimation

Kocabas, M., Athanasiou, N., Black, M. J.

In Computer Vision and Pattern Recognition (CVPR), June 2020 (inproceedings)

Abstract
Human motion is fundamental to understanding behavior. Despite progress on single-image 3D pose and shape estimation, existing video-based state-of-the-art methodsfail to produce accurate and natural motion sequences due to a lack of ground-truth 3D motion data for training. To address this problem, we propose “Video Inference for Body Pose and Shape Estimation” (VIBE), which makes use of an existing large-scale motion capture dataset (AMASS) together with unpaired, in-the-wild, 2D keypoint annotations. Our key novelty is an adversarial learning framework that leverages AMASS to discriminate between real human motions and those produced by our temporal pose and shape regression networks. We define a temporal network architecture and show that adversarial training, at the sequence level, produces kinematically plausible motion sequences without in-the-wild ground-truth 3D labels. We perform extensive experimentation to analyze the importance of motion and demonstrate the effectiveness of VIBE on challenging 3D pose estimation datasets, achieving state-of-the-art performance. Code and pretrained models are available at https://github.com/mkocabas/VIBE

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arXiv code [BibTex]

arXiv code [BibTex]


From Variational to Deterministic Autoencoders
From Variational to Deterministic Autoencoders

Ghosh*, P., Sajjadi*, M. S. M., Vergari, A., Black, M. J., Schölkopf, B.

8th International Conference on Learning Representations (ICLR) , April 2020, *equal contribution (conference) Accepted

Abstract
Variational Autoencoders (VAEs) provide a theoretically-backed framework for deep generative models. However, they often produce “blurry” images, which is linked to their training objective. Sampling in the most popular implementation, the Gaussian VAE, can be interpreted as simply injecting noise to the input of a deterministic decoder. In practice, this simply enforces a smooth latent space structure. We challenge the adoption of the full VAE framework on this specific point in favor of a simpler, deterministic one. Specifically, we investigate how substituting stochasticity with other explicit and implicit regularization schemes can lead to a meaningful latent space without having to force it to conform to an arbitrarily chosen prior. To retrieve a generative mechanism for sampling new data points, we propose to employ an efficient ex-post density estimation step that can be readily adopted both for the proposed deterministic autoencoders as well as to improve sample quality of existing VAEs. We show in a rigorous empirical study that regularized deterministic autoencoding achieves state-of-the-art sample quality on the common MNIST, CIFAR-10 and CelebA datasets.

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arXiv [BibTex]

arXiv [BibTex]


Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations
Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations

Rueegg, N., Lassner, C., Black, M. J., Schindler, K.

In Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), Febuary 2020 (inproceedings)

Abstract
The goal of many computer vision systems is to transform image pixels into 3D representations. Recent popular models use neural networks to regress directly from pixels to 3D object parameters. Such an approach works well when supervision is available, but in problems like human pose and shape estimation, it is difficult to obtain natural images with 3D ground truth. To go one step further, we propose a new architecture that facilitates unsupervised, or lightly supervised, learning. The idea is to break the problem into a series of transformations between increasingly abstract representations. Each step involves a cycle designed to be learnable without annotated training data, and the chain of cycles delivers the final solution. Specifically, we use 2D body part segments as an intermediate representation that contains enough information to be lifted to 3D, and at the same time is simple enough to be learned in an unsupervised way. We demonstrate the method by learning 3D human pose and shape from un-paired and un-annotated images. We also explore varying amounts of paired data and show that cycling greatly alleviates the need for paired data. While we present results for modeling humans, our formulation is general and can be applied to other vision problems.

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pdf [BibTex]

pdf [BibTex]


Towards 5-DoF Control of an Untethered Magnetic Millirobot via MRI Gradient Coils
Towards 5-DoF Control of an Untethered Magnetic Millirobot via MRI Gradient Coils

Onder Erin, D. A. M. E. T., Sitti, M.

In IEEE International Conference on Robotics and Automation (ICRA), 2020 (inproceedings)

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[BibTex]

[BibTex]

2010


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Adhesion recovery and passive peeling in a wall climbing robot using adhesives

Kute, C., Murphy, M. P., Mengüç, Y., Sitti, M.

In Robotics and Automation (ICRA), 2010 IEEE International Conference on, pages: 2797-2802, 2010 (inproceedings)

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[BibTex]

2010


[BibTex]


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Absence of element specific ferromagnetism in Co doped ZnO investigated by soft X-ray resonant reflectivity

Goering, E., Brück, S., Tietze, T., Jakob, G., Gacic, M., Adrian, H.

In 200, Glasgow, Scotland, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Probing the local magnetization dynamics in large systems with spatial inhomogeneity

Li, J, Lee, M.-S., Amaladass, E., He, W., Eimüller, T.

In 200, Glasgow, Scotland, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Wetting of grain boundaries in Al by the solid Al3Mg2 phase

Straumal, B. B., Baretzky, B., Kogtenkova, O. A., Straumal, A. B., Sidorenko, A. S.

In 45, pages: 2057-2061, Athens, Greek, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Damping of near-adiabatic magnetization dynamics by excitations of electron-hole pairs

Seib, J., Steiauf, D., Fähnle, M.

In 200, Karlsruhe, Germany, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Comparison of linear and nonlinear buck converter models with varying compensator gain values for design optimization

Sattler, Michael, Lui, Yusi, Edrington, Chris S

In North American Power Symposium (NAPS), 2010, pages: 1-7, 2010 (inproceedings)

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[BibTex]

[BibTex]


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Magnetization reversal of Fe/Gd multilayers on self-assembled arrays of nanospheres

Amaladass, E., Eimüller, T., Ludescher, B., Tyliszczak, T., Schütz, G.

In 200, Glasgow, Scotland, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Enhancing the performance of Bio-inspired adhesives

Chung, H., Glass, P., Sitti, M., Washburn, N. R.

In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 240, 2010 (inproceedings)

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[BibTex]

[BibTex]


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Control performance simulation in the design of a flapping wing micro-aerial vehicle

Hines, L. L., Arabagi, V., Sitti, M.

In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pages: 1090-1095, 2010 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Contact angles by the solid-phase grain boundary wetting (coverage) in the Co-Cu system

Straumal, B. B., Kogtenkova, O. A., Straumal, A. B., Kuchyeyev, Y. O., Baretzky, B.

In 45, pages: 4271-4275, Glasgow, Scotland, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Unusual super-ductility at room temperature in an ultrafine-grained aluminum alloy

Valiev, R. Z., Murashkin, M. Y., Kilmametov, A., Straumal, B., Chinh, N. Q., Langdon, T.

In 45, pages: 4718-4724, Seattle, WA, USA, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Demagnetization on the fs time-scale by the Elliott-Yafet mechanism

Steiauf, D., Illg, C., Fähnle, M.

In 200, Karlsruhe, Germany, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Surface tension driven water strider robot using circular footpads

Ozcan, O., Wang, H., Taylor, J. D., Sitti, M.

In Robotics and Automation (ICRA), 2010 IEEE International Conference on, pages: 3799-3804, 2010 (inproceedings)

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[BibTex]

[BibTex]


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Handbook of Hydrogen Storage

Hirscher, M.

pages: 353 p., Wiley-VCH, Weinheim, 2010 (book)

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[BibTex]

[BibTex]


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The X-ray microscopy beamline UE46-PGM2 at BESSY

Follath, R., Schmidt, J. S., Weigand, M., Fauth, K.

In 10th International Conference on Synchrotron Radiation Instrumentation, 1234, pages: 323-326, AIP Conference Proceedings, American Institute of Physics, Melbourne, Australia, 2010 (inproceedings)

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DOI [BibTex]

DOI [BibTex]

2006


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Ab-initio calculations: I. Basic principles of the density functional electron theory and combination with phenomenological theories

Fähnle, M.

In Structural defects in ordered alloys and intermetallics. Characterization and modelling, pages: IX-1-IX-10, COST and CNRS, Bonascre [Ariege, France], 2006 (inproceedings)

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[BibTex]

2006


[BibTex]


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Hard magnetic FePt thin films and nanostructures in L1(0) phases

Goll, D., Breitling, A., Goo, N. H., Sigle, W., Hirscher, M., Schütz, G.

In 13, pages: 97-101, Beijing, PR China, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Miniature endoscopic capsule robot using biomimetic micro-patterned adhesives

Karagozler, M. E., Cheung, E., Kwon, J., Sitti, M.

In Biomedical Robotics and Biomechatronics, 2006. BioRob 2006. The First IEEE/RAS-EMBS International Conference on, pages: 105-111, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Ab-initio calculations: II. Application to atomic defects, phase diagrams, dislocations

Fähnle, M.

In Structural defects in ordered alloys and intermetallics. Characterization and modelling, pages: XIV-1-XIV-11, COST and CNRS, Bonascre [Ariege, France], 2006 (inproceedings)

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[BibTex]

[BibTex]


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Toward micro wall-climbing robots using biomimetic fibrillar adhesives

Greuter, M., Shah, G., Caprari, G., Tâche, F., Siegwart, R., Sitti, M.

In Proceedings of the 3rd International Symposium on Autonomous Minirobots for Research and Edutainment (AMiRE 2005), pages: 39-46, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Geckobot: A gecko inspired climbing robot using elastomer adhesives

Unver, O., Uneri, A., Aydemir, A., Sitti, M.

In Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on, pages: 2329-2335, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Towards hybrid swimming microrobots: bacteria assisted propulsion of polystyrene beads

Behkam, B., Sitti, M.

In Engineering in Medicine and Biology Society, 2006. EMBS’06. 28th Annual International Conference of the IEEE, pages: 2421-2424, 2006 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Soft microcontact printing with force control using microrobotic assembly based templates

Tafazzoli, A., Sitti, M.

In Advanced Motion Control, 2006. 9th IEEE International Workshop on, pages: 500-505, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Modeling of the supporting legs for designing biomimetic water strider robots

Song, Y. S., Suhr, S. H., Sitti, M.

In Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on, pages: 2303-2310, 2006 (inproceedings)

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[BibTex]

[BibTex]


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A novel water running robot inspired by basilisk lizards

Floyd, S., Keegan, T., Palmisano, J., Sitti, M.

In Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, pages: 5430-5436, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Residual stress analysis in reed pipe brass tongues of historic organs

Manescu, A., Giuliani, A., Fiori, F., Baretzky, B.

In Residual Stresses VII. 7th Europen Conference on Residual Stresses (ECRS7), pages: 969-974, Trans Tech, Berlin [Germany], 2006 (inproceedings)

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[BibTex]

[BibTex]


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Force-controlled microcontact printing using microassembled particle templates

Tafazzoli, A., Pawashe, C., Sitti, M.

In Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on, pages: 263-268, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Waalbot: An agile small-scale wall climbing robot utilizing pressure sensitive adhesives

Murphy, M. P., Tso, W., Tanzini, M., Sitti, M.

In Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, pages: 3411-3416, 2006 (inproceedings)

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[BibTex]

[BibTex]


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High-pressure influence on the kinetics of grain boundary segregation in the Cu-Bi system

Chang, L.-S., Straumal, B., Rabkin, E., Lojkowski, W., Gust, W.

In 258-260, pages: 390-396, Aveiro (Portugal), 2006 (inproceedings)

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[BibTex]

[BibTex]

1999


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Tele-touch feedback of surfaces at the micro/nano scale: Modeling and experiments

Sitti, M., Horighuchi, S., Hashimoto, H.

In Intelligent Robots and Systems, 1999. IROS’99. Proceedings. 1999 IEEE/RSJ International Conference on, 2, pages: 882-888, 1999 (inproceedings)

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[BibTex]

1999


[BibTex]


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Challenge to micro/nanomanipulation using atomic force microscope

Hashimoto, H., Sitti, M.

In Micromechatronics and Human Science, 1999. MHS’99. Proceedings of 1999 International Symposium on, pages: 35-42, 1999 (inproceedings)

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[BibTex]

[BibTex]


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Visualization interface for AFM-based nano-manipulation

Horiguchi, S., Sitti, M., Hashimoto, H.

In Industrial Electronics, 1999. ISIE’99. Proceedings of the IEEE International Symposium on, 1, pages: 310-315, 1999 (inproceedings)

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[BibTex]

[BibTex]


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Tele-nanorobotics 2-d manipulation of micro/nanoparticles using afm

Sitti, M., Horiguchi, S., Hashimoto, H.

In Advanced Intelligent Mechatronics, 1999. Proceedings. 1999 IEEE/ASME International Conference on, pages: 786-786, 1999 (inproceedings)

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[BibTex]

[BibTex]


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Two-dimensional fine particle positioning using a piezoresistive cantilever as a micro/nano-manipulator

Sitti, M., Hashimoto, H.

In Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on, 4, pages: 2729-2735, 1999 (inproceedings)

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[BibTex]

[BibTex]