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2018


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

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

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

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

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link (url) DOI Project Page [BibTex]

2018


link (url) DOI Project Page [BibTex]


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

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

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

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

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DOI [BibTex]

DOI [BibTex]


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

Serhat, G., Basdogan, I.

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

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

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.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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

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

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

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

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Robust Physics-based Motion Retargeting with Realistic Body Shapes
Robust Physics-based Motion Retargeting with Realistic Body Shapes

Borno, M. A., Righetti, L., Black, M. J., Delp, S. L., Fiume, E., Romero, J.

Computer Graphics Forum, 37, pages: 6:1-12, July 2018 (article)

Abstract
Motion capture is often retargeted to new, and sometimes drastically different, characters. When the characters take on realistic human shapes, however, we become more sensitive to the motion looking right. This means adapting it to be consistent with the physical constraints imposed by different body shapes. We show how to take realistic 3D human shapes, approximate them using a simplified representation, and animate them so that they move realistically using physically-based retargeting. We develop a novel spacetime optimization approach that learns and robustly adapts physical controllers to new bodies and constraints. The approach automatically adapts the motion of the mocap subject to the body shape of a target subject. This motion respects the physical properties of the new body and every body shape results in a different and appropriate movement. This makes it easy to create a varied set of motions from a single mocap sequence by simply varying the characters. In an interactive environment, successful retargeting requires adapting the motion to unexpected external forces. We achieve robustness to such forces using a novel LQR-tree formulation. We show that the simulated motions look appropriate to each character’s anatomy and their actions are robust to perturbations.

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pdf video Project Page Project Page [BibTex]

pdf video Project Page Project Page [BibTex]


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

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

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

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

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DOI [BibTex]

DOI [BibTex]


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Rational metareasoning and the plasticity of cognitive control

Lieder, F., Shenhav, A., Musslick, S., Griffiths, T. L.

PLOS Computational Biology, 14(4):e1006043, Public Library of Science, April 2018 (article)

Abstract
The human brain has the impressive capacity to adapt how it processes information to high-level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people’s ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure.

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Rational metareasoning and the plasticity of cognitive control DOI Project Page Project Page [BibTex]

Rational metareasoning and the plasticity of cognitive control DOI Project Page Project Page [BibTex]


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Automatically Rating Trainee Skill at a Pediatric Laparoscopic Suturing Task

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

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

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DOI [BibTex]

DOI [BibTex]


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

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

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

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

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DOI [BibTex]

DOI [BibTex]


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

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

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

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

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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

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

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

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

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Over-Representation of Extreme Events in Decision Making Reflects Rational Use of Cognitive Resources

Lieder, F., Griffiths, T. L., Hsu, M.

Psychological Review, 125(1):1-32, January 2018 (article)

Abstract
People’s decisions and judgments are disproportionately swayed by improbable but extreme eventualities, such as terrorism, that come to mind easily. This article explores whether such availability biases can be reconciled with rational information processing by taking into account the fact that decision-makers value their time and have limited cognitive resources. Our analysis suggests that to make optimal use of their finite time decision-makers should over-represent the most important potential consequences relative to less important, put potentially more probable, outcomes. To evaluate this account we derive and test a model we call utility-weighted sampling. Utility-weighted sampling estimates the expected utility of potential actions by simulating their outcomes. Critically, outcomes with more extreme utilities have a higher probability of being simulated. We demonstrate that this model can explain not only people’s availability bias in judging the frequency of extreme events but also a wide range of cognitive biases in decisions from experience, decisions from description, and memory recall.

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DOI [BibTex]

DOI [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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The Computational Challenges of Pursuing Multiple Goals: Network Structure of Goal Systems Predicts Human Performance

Reichman, D., Lieder, F., Bourgin, D. D., Talmon, N., Griffiths, T. L.

PsyArXiv, 2018 (article)

Abstract
Extant psychological theories attribute people’s failure to achieve their goals primarily to failures of self-control, insufficient motivation, or lacking skills. We develop a complementary theory specifying conditions under which the computational complexity of making the right decisions becomes prohibitive of goal achievement regardless of skill or motivation. We support our theory by predicting human performance from factors determining the computational complexity of selecting the optimal set of means for goal achievement. Following previous theories of goal pursuit, we express the relationship between goals and means as a bipartite graph where edges between means and goals indicate which means can be used to achieve which goals. This allows us to map two computational challenges that arise in goal achievement onto two classic combinatorial optimization problems: Set Cover and Maximum Coverage. While these problems are believed to be computationally intractable on general networks, their solution can be nevertheless efficiently approximated when the structure of the network resembles a tree. Thus, our initial prediction was that people should perform better with goal systems that are more tree-like. In addition, our theory predicted that people’s performance at selecting means should be a U-shaped function of the average number of goals each means is relevant to and the average number of means through which each goal could be accomplished. Here we report on six behavioral experiments which confirmed these predictions. Our results suggest that combinatorial parameters that are instrumental to algorithm design can also be useful for understanding when and why people struggle to pursue their goals effectively.

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DOI [BibTex]

DOI [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.

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vardar_toh2018 DOI [BibTex]

vardar_toh2018 DOI [BibTex]


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Learning a Structured Neural Network Policy for a Hopping Task.

Viereck, J., Kozolinsky, J., Herzog, A., Righetti, L.

IEEE Robotics and Automation Letters, 3(4):4092-4099, October 2018 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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The Impact of Robotics and Automation on Working Conditions and Employment [Ethical, Legal, and Societal Issues]

Pham, Q., Madhavan, R., Righetti, L., Smart, W., Chatila, R.

IEEE Robotics and Automation Magazine, 25(2):126-128, June 2018 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Lethal Autonomous Weapon Systems [Ethical, Legal, and Societal Issues]

Righetti, L., Pham, Q., Madhavan, R., Chatila, R.

IEEE Robotics \& Automation Magazine, 25(1):123-126, March 2018 (article)

Abstract
The topic of lethal autonomous weapon systems has recently caught public attention due to extensive news coverage and apocalyptic declarations from famous scientists and technologists. Weapon systems with increasing autonomy are being developed due to fast improvements in machine learning, robotics, and automation in general. These developments raise important and complex security, legal, ethical, societal, and technological issues that are being extensively discussed by scholars, nongovernmental organizations (NGOs), militaries, governments, and the international community. Unfortunately, the robotics community has stayed out of the debate, for the most part, despite being the main provider of autonomous technologies. In this column, we review the main issues raised by the increase of autonomy in weapon systems and the state of the international discussion. We argue that the robotics community has a fundamental role to play in these discussions, for its own sake, to provide the often-missing technical expertise necessary to frame the debate and promote technological development in line with the IEEE Robotics and Automation Society (RAS) objective of advancing technology to benefit humanity.

mg

link (url) DOI [BibTex]

link (url) DOI [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.

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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

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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.

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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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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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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]


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Momentum Control with Hierarchical Inverse Dynamics on a Torque-Controlled Humanoid

Herzog, A., Rotella, N., Mason, S., Grimminger, F., Schaal, S., Righetti, L.

Autonomous Robots, 40(3):473-491, 2016 (article)

Abstract
Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.

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link (url) DOI [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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Burn-in, bias, and the rationality of anchoring

Lieder, F., Griffiths, T. L., Goodman, N. D.

Advances in Neural Information Processing Systems 25, pages: 2699-2707, 2012 (article)

Abstract
Bayesian inference provides a unifying framework for addressing problems in machine learning, artificial intelligence, and robotics, as well as the problems facing the human mind. Unfortunately, exact Bayesian inference is intractable in all but the simplest models. Therefore minds and machines have to approximate Bayesian inference. Approximate inference algorithms can achieve a wide range of time-accuracy tradeoffs, but what is the optimal tradeoff? We investigate time-accuracy tradeoffs using the Metropolis-Hastings algorithm as a metaphor for the mind's inference algorithm(s). We find that reasonably accurate decisions are possible long before the Markov chain has converged to the posterior distribution, i.e. during the period known as burn-in. Therefore the strategy that is optimal subject to the mind's bounded processing speed and opportunity costs may perform so few iterations that the resulting samples are biased towards the initial value. The resulting cognitive process model provides a rational basis for the anchoring-and-adjustment heuristic. The model's quantitative predictions are tested against published data on anchoring in numerical estimation tasks. Our theoretical and empirical results suggest that the anchoring bias is consistent with approximate Bayesian inference.

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link (url) [BibTex]

link (url) [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)

hi

[BibTex]

[BibTex]

2009


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Adaptive Frequency Oscillators and Applications

Righetti, L., Buchli, J., Ijspeert, A.

The Open Cybernetics \& Systemics Journal, 3, pages: 64-69, 2009 (article)

Abstract
In this contribution we present a generic mechanism to transform an oscillator into an adaptive frequency oscillator, which can then dynamically adapt its parameters to learn the frequency of any periodic driving signal. Adaptation is done in a dynamic way: it is part of the dynamical system and not an offline process. This mechanism goes beyond entrainment since it works for any initial frequencies and the learned frequency stays encoded in the system even if the driving signal disappears. Interestingly, this mechanism can easily be applied to a large class of oscillators from harmonic oscillators to relaxation types and strange attractors. Several practical applications of this mechanism are then presented, ranging from adaptive control of compliant robots to frequency analysis of signals and construction of limit cycles of arbitrary shape.

mg

link (url) [BibTex]

2009


link (url) [BibTex]