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2020


Statistical reprogramming of macroscopic self-assembly with dynamic boundaries
Statistical reprogramming of macroscopic self-assembly with dynamic boundaries

Culha, U., Davidson, Z. S., Mastrangeli, M., Sitti, M.

Proceedings of the National Academy of Sciences, 117(21):11306-11313, May 2020 (article)

Abstract
Self-assembly is a ubiquitous process that can generate complex and functional structures via local interactions among a large set of simpler components. The ability to program the self-assembly pathway of component sets elucidates fundamental physics and enables alternative competitive fabrication technologies. Reprogrammability offers further opportunities for tuning structural and material properties but requires reversible selection from multistable self-assembling patterns, which remains a challenge. Here, we show statistical reprogramming of two-dimensional (2D), noncompact self-assembled structures by the dynamic confinement of orbitally shaken and magnetically repulsive millimeter-scale particles. Under a constant shaking regime, we control the rate of radius change of an assembly arena via moving hard boundaries and select among a finite set of self-assembled patterns repeatably and reversibly. By temporarily trapping particles in topologically identified stable states, we also demonstrate 2D reprogrammable stiffness and three-dimensional (3D) magnetic clutching of the self-assembled structures. Our reprogrammable system has prospective implications for the design of granular materials in a multitude of physical scales where out-of-equilibrium self-assembly can be realized with different numbers or types of particles. Our dynamic boundary regulation may also enable robust bottom-up control strategies for novel robotic assembly applications by designing more complex spatiotemporal interactions using mobile robots.

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DOI [BibTex]

2020


DOI [BibTex]


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Adaptation and Robust Learning of Probabilistic Movement Primitives

Gomez-Gonzalez, S., Neumann, G., Schölkopf, B., Peters, J.

IEEE Transactions on Robotics, 36(2):366-379, IEEE, March 2020 (article)

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arXiv DOI Project Page [BibTex]

arXiv DOI Project Page [BibTex]


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Real Time Trajectory Prediction Using Deep Conditional Generative Models

Gomez-Gonzalez, S., Prokudin, S., Schölkopf, B., Peters, J.

IEEE Robotics and Automation Letters, 5(2):970-976, IEEE, January 2020 (article)

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arXiv DOI [BibTex]

arXiv DOI [BibTex]


Thermal Effects on the Crystallization Kinetics, and Interfacial Adhesion of Single-Crystal Phase-Change Gallium
Thermal Effects on the Crystallization Kinetics, and Interfacial Adhesion of Single-Crystal Phase-Change Gallium

Yunusa, M., Lahlou, A., Sitti, M.

Advanced Materials, Wiley Online Library, 2020 (article)

Abstract
Although substrates play an important role upon crystallization of supercooled liquids, the influences of surface temperature and thermal property have remained elusive. Here, the crystallization of supercooled phase‐change gallium (Ga) on substrates with different thermal conductivity is studied. The effect of interfacial temperature on the crystallization kinetics, which dictates thermo‐mechanical stresses between the substrate and the crystallized Ga, is investigated. At an elevated surface temperature, close to the melting point of Ga, an extended single‐crystal growth of Ga on dielectric substrates due to layering effect and annealing is realized without the application of external fields. Adhesive strength at the interfaces depends on the thermal conductivity and initial surface temperature of the substrates. This insight can be applicable to other liquid metals for industrial applications, and sheds more light on phase‐change memory crystallization.

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[BibTex]


Nanoerythrosome-functionalized biohybrid microswimmers
Nanoerythrosome-functionalized biohybrid microswimmers

Buss, N., Yasa, O., Alapan, Y., Akolpoglu, M. B., Sitti, M.

APL Bioengineering, 4, AIP Publishing LLC, 2020 (article)

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[BibTex]

[BibTex]


Injectable Nanoelectrodes Enable Wireless Deep Brain Stimulation of Native Tissue in Freely Moving Mice
Injectable Nanoelectrodes Enable Wireless Deep Brain Stimulation of Native Tissue in Freely Moving Mice

Kozielski, K. L., Jahanshahi, A., Gilbert, H. B., Yu, Y., Erin, O., Francisco, D., Alosaimi, F., Temel, Y., Sitti, M.

bioRxiv, Cold Spring Harbor Laboratory, 2020 (article)

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[BibTex]

[BibTex]


Magnetically Actuated Soft Capsule Endoscope for Fine-Needle Biopsy
Magnetically Actuated Soft Capsule Endoscope for Fine-Needle Biopsy

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

Soft robotics, Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New …, 2020 (article)

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[BibTex]

[BibTex]


Mechanical coupling of puller and pusher active microswimmers influences motility
Mechanical coupling of puller and pusher active microswimmers influences motility

Singh, A. V., Kishore, V., Santamauro, G., Yasa, O., Bill, J., Sitti, M.

Langmuir, ACS Publications, 2020 (article)

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[BibTex]


Microribbons composed of directionally self-assembled nanoflakes as highly stretchable ionic neural electrodes
Microribbons composed of directionally self-assembled nanoflakes as highly stretchable ionic neural electrodes

Zhang, M., Guo, R., Chen, K., Wang, Y., Niu, J., Guo, Y., Zhang, Y., Yin, Z., Xia, K., Zhou, B., Wang, H., He, W., Liu, J., Sitti, M., Zhang, Y.

Proceedings of the National Academy of Sciences, National Academy of Sciences, 2020 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Controlling two-dimensional collective formation and cooperative behavior of magnetic microrobot swarms
Controlling two-dimensional collective formation and cooperative behavior of magnetic microrobot swarms

Dong, X., Sitti, M.

The International Journal of Robotics Research, 2020 (article)

Abstract
Magnetically actuated mobile microrobots can access distant, enclosed, and small spaces, such as inside microfluidic channels and the human body, making them appealing for minimally invasive tasks. Despite their simplicity when scaling down, creating collective microrobots that can work closely and cooperatively, as well as reconfigure their formations for different tasks, would significantly enhance their capabilities such as manipulation of objects. However, a challenge of realizing such cooperative magnetic microrobots is to program and reconfigure their formations and collective motions with under-actuated control signals. This article presents a method of controlling 2D static and time-varying formations among collective self-repelling ferromagnetic microrobots (100 μm to 350 μm in diameter, up to 260 in number) by spatially and temporally programming an external magnetic potential energy distribution at the air–water interface or on solid surfaces. A general design method is introduced to program external magnetic potential energy using ferromagnets. A predictive model of the collective system is also presented to predict the formation and guide the design procedure. With the proposed method, versatile complex static formations are experimentally demonstrated and the programmability and scaling effects of formations are analyzed. We also demonstrate the collective mobility of these magnetic microrobots by controlling them to exhibit bio-inspired collective behaviors such as aggregation, directional motion with arbitrary swarm headings, and rotational swarming motion. Finally, the functions of the produced microrobotic swarm are demonstrated by controlling them to navigate through cluttered environments and complete reconfigurable cooperative manipulation tasks.

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DOI [BibTex]


Magnetic Resonance Imaging System--Driven Medical Robotics
Magnetic Resonance Imaging System–Driven Medical Robotics

Erin, O., Boyvat, M., Tiryaki, M. E., Phelan, M., Sitti, M.

Advanced Intelligent Systems, 2, Wiley Online Library, 2020 (article)

Abstract
Magnetic resonance imaging (MRI) system–driven medical robotics is an emerging field that aims to use clinical MRI systems not only for medical imaging but also for actuation, localization, and control of medical robots. Submillimeter scale resolution of MR images for soft tissues combined with the electromagnetic gradient coil–based magnetic actuation available inside MR scanners can enable theranostic applications of medical robots for precise image‐guided minimally invasive interventions. MRI‐driven robotics typically does not introduce new MRI instrumentation for actuation but instead focuses on converting already available instrumentation for robotic purposes. To use the advantages of this technology, various medical devices such as untethered mobile magnetic robots and tethered active catheters have been designed to be powered magnetically inside MRI systems. Herein, the state‐of‐the‐art progress, challenges, and future directions of MRI‐driven medical robotic systems are reviewed.

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[BibTex]

[BibTex]


Characterization and Thermal Management of a DC Motor-Driven Resonant Actuator for Miniature Mobile Robots with Oscillating Limbs
Characterization and Thermal Management of a DC Motor-Driven Resonant Actuator for Miniature Mobile Robots with Oscillating Limbs

Colmenares, D., Kania, R., Liu, M., Sitti, M.

arXiv preprint arXiv:2002.00798, 2020 (article)

Abstract
In this paper, we characterize the performance of and develop thermal management solutions for a DC motor-driven resonant actuator developed for flapping wing micro air vehicles. The actuator, a DC micro-gearmotor connected in parallel with a torsional spring, drives reciprocal wing motion. Compared to the gearmotor alone, this design increased torque and power density by 161.1% and 666.8%, respectively, while decreasing the drawn current by 25.8%. Characterization of the actuator, isolated from nonlinear aerodynamic loading, results in standard metrics directly comparable to other actuators. The micro-motor, selected for low weight considerations, operates at high power for limited duration due to thermal effects. To predict system performance, a lumped parameter thermal circuit model was developed. Critical model parameters for this micro-motor, two orders of magnitude smaller than those previously characterized, were identified experimentally. This included the effects of variable winding resistance, bushing friction, speed-dependent forced convection, and the addition of a heatsink. The model was then used to determine a safe operation envelope for the vehicle and to design a weight-optimal heatsink. This actuator design and thermal modeling approach could be applied more generally to improve the performance of any miniature mobile robot or device with motor-driven oscillating limbs or loads.

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[BibTex]


Pros and Cons: Magnetic versus Optical Microrobots
Pros and Cons: Magnetic versus Optical Microrobots

Sitti, M., Wiersma, D. S.

Advanced Materials, Wiley Online Library, 2020 (article)

Abstract
Mobile microrobotics has emerged as a new robotics field within the last decade to create untethered tiny robots that can access and operate in unprecedented, dangerous, or hard‐to‐reach small spaces noninvasively toward disruptive medical, biotechnology, desktop manufacturing, environmental remediation, and other potential applications. Magnetic and optical actuation methods are the most widely used actuation methods in mobile microrobotics currently, in addition to acoustic and biological (cell‐driven) actuation approaches. The pros and cons of these actuation methods are reported here, depending on the given context. They can both enable long‐range, fast, and precise actuation of single or a large number of microrobots in diverse environments. Magnetic actuation has unique potential for medical applications of microrobots inside nontransparent tissues at high penetration depths, while optical actuation is suitable for more biotechnology, lab‐/organ‐on‐a‐chip, and desktop manufacturing types of applications with much less surface penetration depth requirements or with transparent environments. Combining both methods in new robot designs can have a strong potential of combining the pros of both methods. There is still much progress needed in both actuation methods to realize the potential disruptive applications of mobile microrobots in real‐world conditions.

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[BibTex]

[BibTex]


Selectively Controlled Magnetic Microrobots with Opposing Helices
Selectively Controlled Magnetic Microrobots with Opposing Helices

Giltinan, J., Katsamba, P., Wang, W., Lauga, E., Sitti, M.

Applied Physics Letters, 116, AIP Publishing LLC, 2020 (article)

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[BibTex]

[BibTex]


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An Adaptive Optimizer for Measurement-Frugal Variational Algorithms

Kübler, J. M., Arrasmith, A., Cincio, L., Coles, P. J.

Quantum, 4, pages: 263, 2020 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Microscale Polarization Color Pixels from Liquid Crystal Elastomers
Microscale Polarization Color Pixels from Liquid Crystal Elastomers

Guo, Y., Shahsavan, H., Sitti, M.

Advanced Optical Materials, Wiley Online Library, 2020 (article)

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[BibTex]

[BibTex]


Wearable and Stretchable Strain Sensors: Materials, Sensing Mechanisms, and Applications
Wearable and Stretchable Strain Sensors: Materials, Sensing Mechanisms, and Applications

Souri, H., Banerjee, H., Jusufi, A., Radacsi, N., Stokes, A. A., Park, I., Sitti, M., Amjadi, M.

Advanced Intelligent Systems, 2020 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Ultrasound-guided Wireless Tubular Robotic Anchoring System
Ultrasound-guided Wireless Tubular Robotic Anchoring System

Wang, T., Hu, W., Ren, Z., Sitti, M.

IEEE Robotics and Automation Letters, 5, pages: 4859 - 4866, IEEE, 2020 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Cohesive self-organization of mobile microrobotic swarms
Cohesive self-organization of mobile microrobotic swarms

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

arXiv preprint arXiv:1907.05856, 2020 (article)

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[BibTex]

[BibTex]


Bio-inspired Flexible Twisting Wings Increase Lift and Efficiency of a Flapping Wing Micro Air Vehicle
Bio-inspired Flexible Twisting Wings Increase Lift and Efficiency of a Flapping Wing Micro Air Vehicle

Colmenares, D., Kania, R., Zhang, W., Sitti, M.

arXiv preprint arXiv:2001.11586, 2020 (article)

Abstract
We investigate the effect of wing twist flexibility on lift and efficiency of a flapping-wing micro air vehicle capable of liftoff. Wings used previously were chosen to be fully rigid due to modeling and fabrication constraints. However, biological wings are highly flexible and other micro air vehicles have successfully utilized flexible wing structures for specialized tasks. The goal of our study is to determine if dynamic twisting of flexible wings can increase overall aerodynamic lift and efficiency. A flexible twisting wing design was found to increase aerodynamic efficiency by 41.3%, translational lift production by 35.3%, and the effective lift coefficient by 63.7% compared to the rigid-wing design. These results exceed the predictions of quasi-steady blade element models, indicating the need for unsteady computational fluid dynamics simulations of twisted flapping wings.

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[BibTex]

[BibTex]


Acoustically powered surface-slipping mobile microrobots
Acoustically powered surface-slipping mobile microrobots

Aghakhani, A., Yasa, O., Wrede, P., Sitti, M.

Proceedings of the National Academy of Sciences, 117, National Acad Sciences, 2020 (article)

Abstract
Untethered synthetic microrobots have significant potential to revolutionize minimally invasive medical interventions in the future. However, their relatively slow speed and low controllability near surfaces typically are some of the barriers standing in the way of their medical applications. Here, we introduce acoustically powered microrobots with a fast, unidirectional surface-slipping locomotion on both flat and curved surfaces. The proposed three-dimensionally printed, bullet-shaped microrobot contains a spherical air bubble trapped inside its internal body cavity, where the bubble is resonated using acoustic waves. The net fluidic flow due to the bubble oscillation orients the microrobot's axisymmetric axis perpendicular to the wall and then propels it laterally at very high speeds (up to 90 body lengths per second with a body length of 25 µm) while inducing an attractive force toward the wall. To achieve unidirectional locomotion, a small fin is added to the microrobot’s cylindrical body surface, which biases the propulsion direction. For motion direction control, the microrobots are coated anisotropically with a soft magnetic nanofilm layer, allowing steering under a uniform magnetic field. Finally, surface locomotion capability of the microrobots is demonstrated inside a three-dimensional circular cross-sectional microchannel under acoustic actuation. Overall, the combination of acoustic powering and magnetic steering can be effectively utilized to actuate and navigate these microrobots in confined and hard-to-reach body location areas in a minimally invasive fashion.

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[BibTex]

[BibTex]


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Morphology-Dependent Immunogenicity Obliges a Compromise on the Locomotion-Focused Design of Medical Microrobots

Ceren, , Hakan, , Ugur, , Anna-Maria, , Metin,

Science Robotics, 2020 (article) Accepted

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[BibTex]

[BibTex]


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Counterfactual Mean Embedding

Muandet, K., Kanagawa, M., Saengkyongam, S., Marukatat, S.

Journal of Machine Learning Research, 2020 (article) Accepted

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[BibTex]

[BibTex]


Selection for Function: From Chemically Synthesized Prototypes to 3D-Printed Microdevices
Selection for Function: From Chemically Synthesized Prototypes to 3D-Printed Microdevices

Bachmann, F., Giltinan, J., Codutti, A., Klumpp, S., Sitti, M., Faivre, D.

Advanced Intelligent Systems, 2020 (article)

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[BibTex]

[BibTex]


Biosynthetic self-healing materials for soft machines
Biosynthetic self-healing materials for soft machines

Pena-Francesch, A., Jung, H., Demirel, M. C., Sitti, M.

Nature Materials , 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Visual-Inertial Mapping with Non-Linear Factor Recovery

Usenko, V., Demmel, N., Schubert, D., Stückler, J., Cremers, D.

IEEE Robotics and Automation Letters (RA-L), 5, 2020, accepted for presentation at IEEE International Conference on Robotics and Automation (ICRA) 2020, to appear, arXiv:1904.06504 (article)

Abstract
Cameras and inertial measurement units are complementary sensors for ego-motion estimation and environment mapping. Their combination makes visual-inertial odometry (VIO) systems more accurate and robust. For globally consistent mapping, however, combining visual and inertial information is not straightforward. To estimate the motion and geometry with a set of images large baselines are required. Because of that, most systems operate on keyframes that have large time intervals between each other. Inertial data on the other hand quickly degrades with the duration of the intervals and after several seconds of integration, it typically contains only little useful information. In this paper, we propose to extract relevant information for visual-inertial mapping from visual-inertial odometry using non-linear factor recovery. We reconstruct a set of non-linear factors that make an optimal approximation of the information on the trajectory accumulated by VIO. To obtain a globally consistent map we combine these factors with loop-closing constraints using bundle adjustment. The VIO factors make the roll and pitch angles of the global map observable, and improve the robustness and the accuracy of the mapping. In experiments on a public benchmark, we demonstrate superior performance of our method over the state-of-the-art approaches.

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[BibTex]

[BibTex]


Bioinspired underwater locomotion of light-driven liquid crystal gels
Bioinspired underwater locomotion of light-driven liquid crystal gels

Shahsavan, H., Aghakhani, A., Zeng, H., Guo, Y., Davidson, Z. S., Priimagi, A., Sitti, M.

Proceedings of the National Academy of Sciences, National Acad Sciences, 2020 (article)

Abstract
Untethered dynamic shape programming and control of soft materials have significant applications in technologies such as soft robots, medical devices, organ-on-a-chip, and optical devices. Here, we present a solution to remotely actuate and move soft materials underwater in a fast, efficient, and controlled manner using photoresponsive liquid crystal gels (LCGs). LCG constructs with engineered molecular alignment show a low and sharp phase-transition temperature and experience considerable density reduction by light exposure, thereby allowing rapid and reversible shape changes. We demonstrate different modes of underwater locomotion, such as crawling, walking, jumping, and swimming, by localized and time-varying illumination of LCGs. The diverse locomotion modes of smart LCGs can provide a new toolbox for designing efficient light-fueled soft robots in fluid-immersed media.

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[BibTex]

[BibTex]


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Causal Discovery from Heterogeneous/Nonstationary Data

Huang, B., Zhang, K., J., Z., Ramsey, J., Sanchez-Romero, R., Glymour, C., Schölkopf, B.

Journal of Machine Learning Research, 21(89):1-53, 2020 (article)

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link (url) [BibTex]

link (url) [BibTex]


Additive manufacturing of cellulose-based materials with continuous, multidirectional stiffness gradients
Additive manufacturing of cellulose-based materials with continuous, multidirectional stiffness gradients

Giachini, P., Gupta, S., Wang, W., Wood, D., Yunusa, M., Baharlou, E., Sitti, M., Menges, A.

Science Advances, 6, American Association for the Advancement of Science, 2020 (article)

Abstract
Functionally graded materials (FGMs) enable applications in fields such as biomedicine and architecture, but their fabrication suffers from shortcomings in gradient continuity, interfacial bonding, and directional freedom. In addition, most commercial design software fail to incorporate property gradient data, hindering explorations of the design space of FGMs. Here, we leveraged a combined approach of materials engineering and digital processing to enable extrusion-based multimaterial additive manufacturing of cellulose-based tunable viscoelastic materials with continuous, high-contrast, and multidirectional stiffness gradients. A method to engineer sets of cellulose-based materials with similar compositions, yet distinct mechanical and rheological properties, was established. In parallel, a digital workflow was developed to embed gradient information into design models with integrated fabrication path planning. The payoff of integrating these physical and digital tools is the ability to achieve the same stiffness gradient in multiple ways, opening design possibilities previously limited by the rigid coupling of material and geometry.

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[BibTex]

[BibTex]


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Introducing Progress in Biomedical Engineering; Issue 2 Vol 2

Sitti, M.

Progress in Biomedical Engineering, IOP Publishing, 2020 (article)

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[BibTex]

[BibTex]


Multi-wavelength steerable visible light-driven magnetic CoO-TiO2 microswimmers
Multi-wavelength steerable visible light-driven magnetic CoO-TiO2 microswimmers

Sridhar, V., Park, B., Guo, S., van Aken, P. A., Sitti, M.

ACS Applied Materials \& Interfaces, ACS Publications, 2020 (article)

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[BibTex]

[BibTex]

2004


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On the representation, learning and transfer of spatio-temporal movement characteristics

Ilg, W., Bakir, GH., Mezger, J., Giese, M.

International Journal of Humanoid Robotics, 1(4):613-636, December 2004 (article)

ei

[BibTex]

2004


[BibTex]


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Insect-inspired estimation of egomotion

Franz, MO., Chahl, JS., Krapp, HG.

Neural Computation, 16(11):2245-2260, November 2004 (article)

Abstract
Tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during egomotion. In this study, we examine whether a simplified linear model based on the organization principles in tangential neurons can be used to estimate egomotion from the optic flow. We present a theory for the construction of an estimator consisting of a linear combination of optic flow vectors that incorporates prior knowledge both about the distance distribution of the environment, and about the noise and egomotion statistics of the sensor. The estimator is tested on a gantry carrying an omnidirectional vision sensor. The experiments show that the proposed approach leads to accurate and robust estimates of rotation rates, whereas translation estimates are of reasonable quality, albeit less reliable.

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PDF PostScript Web DOI [BibTex]

PDF PostScript Web DOI [BibTex]


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Efficient face detection by a cascaded support-vector machine expansion

Romdhani, S., Torr, P., Schölkopf, B., Blake, A.

Proceedings of The Royal Society of London A, 460(2501):3283-3297, A, November 2004 (article)

Abstract
We describe a fast system for the detection and localization of human faces in images using a nonlinear ‘support-vector machine‘. We approximate the decision surface in terms of a reduced set of expansion vectors and propose a cascaded evaluation which has the property that the full support-vector expansion is only evaluated on the face-like parts of the image, while the largest part of typical images is classified using a single expansion vector (a simpler and more efficient classifier). As a result, only three reduced-set vectors are used, on average, to classify an image patch. Hence, the cascaded evaluation, presented in this paper, offers a thirtyfold speed-up over an evaluation using the full set of reduced-set vectors, which is itself already thirty times faster than classification using all the support vectors.

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Learning kernels from biological networks by maximizing entropy

Tsuda, K., Noble, W.

Bioinformatics, 20(Suppl. 1):i326-i333, August 2004 (article)

Abstract
Motivation: The diffusion kernel is a general method for computing pairwise distances among all nodes in a graph, based on the sum of weighted paths between each pair of nodes. This technique has been used successfully, in conjunction with kernel-based learning methods, to draw inferences from several types of biological networks. Results: We show that computing the diffusion kernel is equivalent to maximizing the von Neumann entropy, subject to a global constraint on the sum of the Euclidean distances between nodes. This global constraint allows for high variance in the pairwise distances. Accordingly, we propose an alternative, locally constrained diffusion kernel, and we demonstrate that the resulting kernel allows for more accurate support vector machine prediction of protein functional classifications from metabolic and protein–protein interaction networks.

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PDF Web [BibTex]

PDF Web [BibTex]


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Masking effect produced by Mach bands on the detection of narrow bars of random polarity

Henning, GB., Hoddinott, KT., Wilson-Smith, ZJ., Hill, NJ.

Journal of the Optical Society of America, 21(8):1379-1387, A, August 2004 (article)

ei

[BibTex]

[BibTex]


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Support Vector Channel Selection in BCI

Lal, T., Schröder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., Schölkopf, B.

IEEE Transactions on Biomedical Engineering, 51(6):1003-1010, June 2004 (article)

Abstract
Designing a Brain Computer Interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying EEG signals we propose the usage of the state of the art feature selection algorithms Recursive Feature Elimination and Zero-Norm Optimization which are based on the training of Support Vector Machines (SVM). These algorithms can provide more accurate solutions than standard filter methods for feature selection. We adapt the methods for the purpose of selecting EEG channels. For a motor imagery paradigm we show that the number of used channels can be reduced significantly without increasing the classification error. The resulting best channels agree well with the expected underlying cortical activity patterns during the mental tasks. Furthermore we show how time dependent task specific information can be visualized.

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DOI [BibTex]

DOI [BibTex]


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Distance-Based Classification with Lipschitz Functions

von Luxburg, U., Bousquet, O.

Journal of Machine Learning Research, 5, pages: 669-695, June 2004 (article)

Abstract
The goal of this article is to develop a framework for large margin classification in metric spaces. We want to find a generalization of linear decision functions for metric spaces and define a corresponding notion of margin such that the decision function separates the training points with a large margin. It will turn out that using Lipschitz functions as decision functions, the inverse of the Lipschitz constant can be interpreted as the size of a margin. In order to construct a clean mathematical setup we isometrically embed the given metric space into a Banach space and the space of Lipschitz functions into its dual space. To analyze the resulting algorithm, we prove several representer theorems. They state that there always exist solutions of the Lipschitz classifier which can be expressed in terms of distance functions to training points. We provide generalization bounds for Lipschitz classifiers in terms of the Rademacher complexities of some Lipschitz function classes. The generality of our approach can be seen from the fact that several well-known algorithms are special cases of the Lipschitz classifier, among them the support vector machine, the linear programming machine, and the 1-nearest neighbor classifier.

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PDF PostScript PDF [BibTex]

PDF PostScript PDF [BibTex]


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cDNA-Microarray Technology in Cartilage Research - Functional Genomics of Osteoarthritis [in German]

Aigner, T., Finger, F., Zien, A., Bartnik, E.

Zeitschrift f{\"u}r Orthop{\"a}die und ihre Grenzgebiete, 142(2):241-247, April 2004 (article)

Abstract
Functional genomics represents a new challenging approach in order to analyze complex diseases such as osteoarthritis on a molecular level. The characterization of the molecular changes of the cartilage cells, the chondrocytes, enables a better understanding of the pathomechanisms of the disease. In particular, the identification and characterization of new target molecules for therapeutic intervention is of interest. Also, potential molecular markers for diagnosis and monitoring of osteoarthritis contribute to a more appropriate patient management. The DNA-microarray technology complements (but does not replace) biochemical and biological research in new disease-relevant genes. Large-scale functional genomics will identify molecular networks such as yet identified players in the anabolic-catabolic balance of articular cartilage as well as disease-relevant intracellular signaling cascades so far rather unknown in articular chondrocytes. However, at the moment it is also important to recognize the limitations of the microarray technology in order to avoid over-interpretation of the results. This might lead to misleading results and prevent to a significant extent a proper use of the potential of this technology in the field of osteoarthritis.

ei

[BibTex]

[BibTex]


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A Compression Approach to Support Vector Model Selection

von Luxburg, U., Bousquet, O., Schölkopf, B.

Journal of Machine Learning Research, 5, pages: 293-323, April 2004 (article)

Abstract
In this paper we investigate connections between statistical learning theory and data compression on the basis of support vector machine (SVM) model selection. Inspired by several generalization bounds we construct "compression coefficients" for SVMs which measure the amount by which the training labels can be compressed by a code built from the separating hyperplane. The main idea is to relate the coding precision to geometrical concepts such as the width of the margin or the shape of the data in the feature space. The so derived compression coefficients combine well known quantities such as the radius-margin term R^2/rho^2, the eigenvalues of the kernel matrix, and the number of support vectors. To test whether they are useful in practice we ran model selection experiments on benchmark data sets. As a result we found that compression coefficients can fairly accurately predict the parameters for which the test error is minimized.

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PDF [BibTex]

PDF [BibTex]


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Experimentally optimal v in support vector regression for different noise models and parameter settings

Chalimourda, A., Schölkopf, B., Smola, A.

Neural Networks, 17(1):127-141, January 2004 (article)

Abstract
In Support Vector (SV) regression, a parameter ν controls the number of Support Vectors and the number of points that come to lie outside of the so-called var epsilon-insensitive tube. For various noise models and SV parameter settings, we experimentally determine the values of ν that lead to the lowest generalization error. We find good agreement with the values that had previously been predicted by a theoretical argument based on the asymptotic efficiency of a simplified model of SV regression. As a side effect of the experiments, valuable information about the generalization behavior of the remaining SVM parameters and their dependencies is gained. The experimental findings are valid even for complex ‘real-world’ data sets. Based on our results on the role of the ν-SVM parameters, we discuss various model selection methods.

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PDF DOI [BibTex]

PDF DOI [BibTex]