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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.

hi

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.

hi

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.

hi

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.

hi

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.

hi

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.

hi

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)

hi

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.

hi pi

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.

hi

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.

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Numerical Quadrature for Probabilistic Policy Search

Vinogradska, J., Bischoff, B., Achterhold, J., Koller, T., Peters, J.

IEEE Transactions on Pattern Analysis and Machine Intelligence, pages: 1-1, 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)

hi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras

Matsuki, H., von Stumberg, L., Usenko, V., Stueckler, J., Cremers, D.

IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS), Robotics and Automation Letters (RA-L), IEEE, 2018 (article)

ev

[BibTex]

[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.

avg

pdf Project Page [BibTex]

pdf Project Page [BibTex]


Tactile Masking by Electrovibration
Tactile Masking by Electrovibration

Vardar, Y., Güçlü, B., Basdogan, C.

IEEE Transactions on Haptics, 11(4):623-635, 2018 (article)

Abstract
Future touch screen applications will include multiple tactile stimuli displayed simultaneously or consecutively to single finger or multiple fingers. These applications should be designed by considering human tactile masking mechanism since it is known that presenting one stimulus may interfere with the perception of the other. In this study, we investigate the effect of masking on tactile perception of electrovibration displayed on touch screens. Through conducting psychophysical experiments with nine subjects, we measured the masked thresholds of sinusoidal electrovibration bursts (125 Hz) under two masking conditions: simultaneous and pedestal. The masking stimuli were noise bursts, applied at five different sensation levels varying from 2 to 22 dB SL, also presented by electrovibration. For each subject, the detection thresholds were elevated as linear functions of masking levels for both masking types. We observed that the masking effectiveness was larger with pedestal masking than simultaneous masking. Moreover, in order to investigate the effect of tactile masking on our haptic perception of edge sharpness, we compared the perceived sharpness of edges separating two textured regions displayed with and without various masking stimuli. Our results suggest that sharpness perception depends on the local contrast between background and foreground stimuli, which varies as a function of masking amplitude and activation levels of frequency-dependent psychophysical channels.

hi

vardar_toh2018 DOI [BibTex]

vardar_toh2018 DOI [BibTex]


Object Scene Flow
Object Scene Flow

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

ISPRS Journal of Photogrammetry and Remote Sensing, 2018 (article)

Abstract
This work investigates the estimation of dense three-dimensional motion fields, commonly referred to as scene flow. While great progress has been made in recent years, large displacements and adverse imaging conditions as observed in natural outdoor environments are still very challenging for current approaches to reconstruction and motion estimation. In this paper, we propose a unified random field model which reasons jointly about 3D scene flow as well as the location, shape and motion of vehicles in the observed scene. We formulate the problem as the task of decomposing the scene into a small number of rigidly moving objects sharing the same motion parameters. Thus, our formulation effectively introduces long-range spatial dependencies which commonly employed local rigidity priors are lacking. Our inference algorithm then estimates the association of image segments and object hypotheses together with their three-dimensional shape and motion. We demonstrate the potential of the proposed approach by introducing a novel challenging scene flow benchmark which allows for a thorough comparison of the proposed scene flow approach with respect to various baseline models. In contrast to previous benchmarks, our evaluation is the first to provide stereo and optical flow ground truth for dynamic real-world urban scenes at large scale. Our experiments reveal that rigid motion segmentation can be utilized as an effective regularizer for the scene flow problem, improving upon existing two-frame scene flow methods. At the same time, our method yields plausible object segmentations without requiring an explicitly trained recognition model for a specific object class.

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Project Page [BibTex]

Project Page [BibTex]

2016


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An electro-active polymer based lens module for dynamically varying focal system

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

Applied Physics Letters, 109(14):141908, October 2016 (article)

Abstract
We demonstrate a polymer-based active-lens module allowing a dynamic focus controllable optical system with a wide tunable range. The active-lens module is composed of parallelized two active- lenses with a convex and a concave shaped hemispherical lens structure, respectively. Under opera- tion with dynamic input voltage signals, each active-lens produces translational movement bi-directionally responding to a hybrid driving force that is a combination of an electro-active response of a thin dielectric elastomer membrane and an electro-static attraction force. Since the proposed active lens module widely modulates a gap-distance between lens-elements, an optical system based on the active-lens module provides widely-variable focusing for selective imaging of objects in arbitrary position.

hi

link (url) DOI [BibTex]

2016


link (url) DOI [BibTex]


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Wrinkle structures formed by formulating UV-crosslinkable liquid prepolymers

Park, S. K., Kwark, Y., Nam, S., Park, S., Park, B., Yun, S., Moon, J., Lee, J., Yu, B., Kyung, K.

Polymer, 99, pages: 447-452, September 2016 (article)

Abstract
Artificial wrinkles have recently been in the spotlight due to their potential use in high-tech applications. A spontaneously wrinkled film can be fabricated from UV-crosslinkable liquid prepolymers. Here, we controlled the wrinkle formation by simply formulating two UV-crosslinkable liquid prepolymers, tetraethylene glycol bis(4-ethenyl-2,3,5,6-tetrafluorophenyl) ether (TEGDSt) and tetraethylene glycol diacrylate (TEGDA). The wrinkles were formed from the TEGDSt/TEGDA formulated prepolymer layers containing up to 30 wt% of TEGDA. The wrinkle formation depended upon the rate of photo-crosslinking reaction of the formulated prepolymers. The first order apparent rate constant, kapp, was between ca. 5.7 × 10−3 and 12.2 × 10−3 s−1 for the wrinkle formation. The wrinkle structures were modulated within the kapp mainly due to variation in the extent of shrinkage of the formulated prepolymer layers with the content of TEGDA

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Objective assessment of robotic surgical skill using instrument contact vibrations

Gomez, E. D., Aggarwal, R., McMahan, W., Bark, K., Kuchenbecker, K. J.

Surgical Endoscopy, 30(4):1419-1431, 2016 (article)

hi

[BibTex]

[BibTex]


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Cutaneous Feedback of Fingertip Deformation and Vibration for Palpation in Robotic Surgery

Pacchierotti, C., Prattichizzo, D., Kuchenbecker, K. J.

IEEE Transactions on Biomedical Engineering, 63(2):278-287, February 2016 (article)

hi

[BibTex]

[BibTex]


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Structure modulated electrostatic deformable mirror for focus and geometry control

Nam, S., Park, S., Yun, S., Park, B., Park, S. K., Kyung, K.

Optics Express, 24(1):55-66, OSA, January 2016 (article)

Abstract
We suggest a way to electrostatically control deformed geometry of an electrostatic deformable mirror (EDM) based on geometric modulation of a basement. The EDM is composed of a metal coated elastomeric membrane (active mirror) and a polymeric basement with electrode (ground). When an electrical voltage is applied across the components, the active mirror deforms toward the stationary basement responding to electrostatic attraction force in an air gap. Since the differentiated gap distance can induce change in electrostatic force distribution between the active mirror and the basement, the EDMs are capable of controlling deformed geometry of the active mirror with different basement structures (concave, flat, and protrusive). The modulation of the deformed geometry leads to significant change in the range of the focal length of the EDMs. Even under dynamic operations, the EDM shows fairly consistent and large deformation enough to change focal length in a wide frequency range (1~175 Hz). The geometric modulation of the active mirror with dynamic focus tunability can allow the EDM to be an active mirror lens for optical zoom devices as well as an optical component controlling field of view.

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Peripheral vs. central determinants of vibrotactile adaptation

Klöcker, A., Gueorguiev, D., Thonnard, J. L., Mouraux, A.

Journal of Neurophysiology, 115(2):685-691, 2016, PMID: 26581868 (article)

Abstract
Long-lasting mechanical vibrations applied to the skin induce a reversible decrease in the perception of vibration at the stimulated skin site. This phenomenon of vibrotactile adaptation has been studied extensively, yet there is still no clear consensus on the mechanisms leading to vibrotactile adaptation. In particular, the respective contributions of 1) changes affecting mechanical skin impedance, 2) peripheral processes, and 3) central processes are largely unknown. Here we used direct electrical stimulation of nerve fibers to bypass mechanical transduction processes and thereby explore the possible contribution of central vs. peripheral processes to vibrotactile adaptation. Three experiments were conducted. In the first, adaptation was induced with mechanical vibration of the fingertip (51- or 251-Hz vibration delivered for 8 min, at 40× detection threshold). In the second, we attempted to induce adaptation with transcutaneous electrical stimulation of the median nerve (51- or 251-Hz constant-current pulses delivered for 8 min, at 1.5× detection threshold). Vibrotactile detection thresholds were measured before and after adaptation. Mechanical stimulation induced a clear increase of vibrotactile detection thresholds. In contrast, thresholds were unaffected by electrical stimulation. In the third experiment, we assessed the effect of mechanical adaptation on the detection thresholds to transcutaneous electrical nerve stimuli, measured before and after adaptation. Electrical detection thresholds were unaffected by the mechanical adaptation. Taken together, our results suggest that vibrotactile adaptation is predominantly the consequence of peripheral mechanoreceptor processes and/or changes in biomechanical properties of the skin.

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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NimbRo Explorer: Semi-Autonomous Exploration and Mobile Manipulation in Rough Terrain

Stueckler, J., Schwarz, M., Schadler, M., Topalidou-Kyniazopoulou, A., Behnke, S.

Journal of Field Robotics (JFR), 33(4):411-430, Wiley, 2016 (article)

ev

[BibTex]

[BibTex]


Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring
Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring

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

Arxiv, 2016 (article)

Abstract
We present a new notion of probabilistic duality for random variables involving mixture distributions. Using this notion, we show how to implement a highly-parallelizable Gibbs sampler for weakly coupled discrete pairwise graphical models with strictly positive factors that requires almost no preprocessing and is easy to implement. Moreover, we show how our method can be combined with blocking to improve mixing. Even though our method leads to inferior mixing times compared to a sequential Gibbs sampler, we argue that our method is still very useful for large dynamic networks, where factors are added and removed on a continuous basis, as it is hard to maintain a graph coloring in this setup. Similarly, our method is useful for parallelizing Gibbs sampling in graphical models that do not allow for graph colorings with a small number of colors such as densely connected graphs.

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pdf [BibTex]


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Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren’t

Chennu, S., Noreika, V., Gueorguiev, D., Shtyrov, Y., Bekinschtein, T. A., Henson, R.

Journal of Neuroscience, 36(32):8305-8316, Society for Neuroscience, 2016 (article)

Abstract
There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called {\textquotedblleft}mismatch response{\textquotedblright}). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an {\textquotedblleft}omission{\textquotedblright} response). This situation arguably provides a more direct measure of {\textquotedblleft}top-down{\textquotedblright} predictions in the absence of confounding {\textquotedblleft}bottom-up{\textquotedblright} input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of {\textquotedblleft}bottom-up{\textquotedblright} stimuli with the presence versus absence of {\textquotedblleft}top-down{\textquotedblright} attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward {\textquotedblleft}prediction{\textquotedblright} connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction.SIGNIFICANCE STATEMENT Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known {\textquotedblleft}mismatch response.{\textquotedblright} But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain{\textquoteright}s electromagnetic activity, we show that it also generates an {\textquotedblleft}omission response{\textquotedblright} that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain{\textquoteright}s prediction of the future.

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Multi-Layered Mapping and Navigation for Autonomous Micro Aerial Vehicles

Droeschel, D., Nieuwenhuisen, M., Beul, M., Stueckler, J., Holz, D., Behnke, S.

Journal of Field Robotics (JFR), 33(4):451-475, 2016 (article)

ev

[BibTex]

[BibTex]


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Touch uses frictional cues to discriminate flat materials

Gueorguiev, D., Bochereau, S., Mouraux, A., Hayward, V., Thonnard, J.

Scientific reports, 6, pages: 25553, Nature Publishing Group, 2016 (article)

hi

[BibTex]

[BibTex]


Map-Based Probabilistic Visual Self-Localization
Map-Based Probabilistic Visual Self-Localization

Brubaker, M. A., Geiger, A., Urtasun, R.

IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2016 (article)

Abstract
Accurate and efficient self-localization is a critical problem for autonomous systems. This paper describes an affordable solution to vehicle self-localization which uses odometry computed from two video cameras and road maps as the sole inputs. The core of the method is a probabilistic model for which an efficient approximate inference algorithm is derived. The inference algorithm is able to utilize distributed computation in order to meet the real-time requirements of autonomous systems in some instances. Because of the probabilistic nature of the model the method is capable of coping with various sources of uncertainty including noise in the visual odometry and inherent ambiguities in the map (e.g., in a Manhattan world). By exploiting freely available, community developed maps and visual odometry measurements, the proposed method is able to localize a vehicle to 4m on average after 52 seconds of driving on maps which contain more than 2,150km of drivable roads.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]

2012


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Evaluation of Tactile Feedback Methods for Wrist Rotation Guidance

Stanley, A. A., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 5(3):240-251, July 2012 (article)

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[BibTex]

2012


[BibTex]


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Creating realistic virtual textures from contact acceleration data

Romano, J. M., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 5(2):109-119, April 2012, Cover article (article)

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[BibTex]

[BibTex]


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RoboCup@Home: Demonstrating Everyday Manipulation Skills in RoboCup@Home

Stueckler, J., Holz, D., Behnke, S.

IEEE Robotics and Automation Magazine (RAM), 19(2):34-42, 2012 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Construct Validity of Instrument Vibrations as a Measure of Robotic Surgical Skill

Gomez, E. D., Bark, K., Rivera, C., McMahan, W., Remington, A., Lee, D. I., Williams, N., Murayama, K., Dumon, K., Kuchenbecker, K. J.

Journal of the American College of Surgeons, 215(3):S119-120, Chicago, Illinois, USA, 2012, Oral presentation given by Gomez at the {\em American College of Surgeons (ACS) Clinical Congress} (article)

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[BibTex]

[BibTex]

2006


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Induced Master Motion in Force-Reflecting Teleoperation

Kuchenbecker, K. J., Niemeyer, G.

ASME Journal of Dynamic Systems, Measurement, and Control, 128(4):800-810, December 2006 (article)

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[BibTex]

2006


[BibTex]


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Improving Contact Realism Through Event-Based Haptic Feedback

Kuchenbecker, K. J., Fiene, J. P., Niemeyer, G.

IEEE Transactions on Visualization and Computer Graphics, 12(2):219-230, March 2006 (article)

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[BibTex]

[BibTex]