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2018


A Value-Driven Eldercare Robot: Virtual and Physical Instantiations of a Case-Supported Principle-Based Behavior Paradigm
A Value-Driven Eldercare Robot: Virtual and Physical Instantiations of a Case-Supported Principle-Based Behavior Paradigm

Anderson, M., Anderson, S., Berenz, V.

Proceedings of the IEEE, pages: 1,15, October 2018 (article)

Abstract
In this paper, a case-supported principle-based behavior paradigm is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous systems are apt to be deployed and for the actions they are liable to undertake. We believe that this is the case since we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles that balance these features when they are in conflict. Such principles not only help ensure ethical behavior of complex and dynamic systems but also can serve as a basis for justification of this behavior. The requirements, methods, implementation, and evaluation components of the paradigm are detailed as well as its instantiation in both a simulated and real robot functioning in the domain of eldercare.

am

link (url) DOI [BibTex]

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]

link (url) DOI Project Page [BibTex]


Playful: Reactive Programming for Orchestrating Robotic Behavior
Playful: Reactive Programming for Orchestrating Robotic Behavior

Berenz, V., Schaal, S.

IEEE Robotics Automation Magazine, 25(3):49-60, September 2018 (article) In press

Abstract
For many service robots, reactivity to changes in their surroundings is a must. However, developing software suitable for dynamic environments is difficult. Existing robotic middleware allows engineers to design behavior graphs by organizing communication between components. But because these graphs are structurally inflexible, they hardly support the development of complex reactive behavior. To address this limitation, we propose Playful, a software platform that applies reactive programming to the specification of robotic behavior.

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playful website playful_IEEE_RAM link (url) DOI [BibTex]


ClusterNet: Instance Segmentation in RGB-D Images
ClusterNet: Instance Segmentation in RGB-D Images

Shao, L., Tian, Y., Bohg, J.

arXiv, September 2018, Submitted to ICRA'19 (article) Submitted

Abstract
We propose a method for instance-level segmentation that uses RGB-D data as input and provides detailed information about the location, geometry and number of {\em individual\/} objects in the scene. This level of understanding is fundamental for autonomous robots. It enables safe and robust decision-making under the large uncertainty of the real-world. In our model, we propose to use the first and second order moments of the object occupancy function to represent an object instance. We train an hourglass Deep Neural Network (DNN) where each pixel in the output votes for the 3D position of the corresponding object center and for the object's size and pose. The final instance segmentation is achieved through clustering in the space of moments. The object-centric training loss is defined on the output of the clustering. Our method outperforms the state-of-the-art instance segmentation method on our synthesized dataset. We show that our method generalizes well on real-world data achieving visually better segmentation results.

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link (url) [BibTex]

link (url) [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]


Real-time Perception meets Reactive Motion Generation
Real-time Perception meets Reactive Motion Generation

(Best Systems Paper Finalists - Amazon Robotics Best Paper Awards in Manipulation)

Kappler, D., Meier, F., Issac, J., Mainprice, J., Garcia Cifuentes, C., Wüthrich, M., Berenz, V., Schaal, S., Ratliff, N., Bohg, J.

IEEE Robotics and Automation Letters, 3(3):1864-1871, July 2018 (article)

Abstract
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. Our approach emphasizes the importance of continuous, real-time perception and its tight integration with reactive motion generation methods. We present a fully integrated system where real-time object and robot tracking as well as ambient world modeling provides the necessary input to feedback controllers and continuous motion optimizers. Specifically, they provide attractive and repulsive potentials based on which the controllers and motion optimizer can online compute movement policies at different time intervals. We extensively evaluate the proposed system on a real robotic platform in four scenarios that exhibit either challenging workspace geometry or a dynamic environment. We compare the proposed integrated system with a more traditional sense-plan-act approach that is still widely used. In 333 experiments, we show the robustness and accuracy of the proposed system.

am

arxiv video video link (url) DOI Project Page [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)

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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Distributed Event-Based State Estimation for Networked Systems: An LMI Approach

Muehlebach, M., Trimpe, S.

IEEE Transactions on Automatic Control, 63(1):269-276, January 2018 (article)

am ics

arXiv (extended version) DOI Project Page [BibTex]

arXiv (extended version) DOI Project Page [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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Memristor-enhanced humanoid robot control system–Part I: theory behind the novel memcomputing paradigm

Ascoli, A., Baumann, D., Tetzlaff, R., Chua, L. O., Hild, M.

International Journal of Circuit Theory and Applications, 46(1):155-183, 2018 (article)

am

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]


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Memristor-enhanced humanoid robot control system–Part II: circuit theoretic model and performance analysis

Baumann, D., Ascoli, A., Tetzlaff, R., Chua, L. O., Hild, M.

International Journal of Circuit Theory and Applications, 46(1):184-220, 2018 (article)

am

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.

hi

vardar_toh2018 DOI [BibTex]

vardar_toh2018 DOI [BibTex]

2013


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A Practical System For Recording Instrument Interactions During Live Robotic Surgery

McMahan, W., Gomez, E. D., Chen, L., Bark, K., Nappo, J. C., Koch, E. I., Lee, D. I., Dumon, K., Williams, N., Kuchenbecker, K. J.

Journal of Robotic Surgery, 7(4):351-358, 2013 (article)

hi

[BibTex]

2013


[BibTex]


3-D Object Reconstruction of Symmetric Objects by Fusing Visual and Tactile Sensing
3-D Object Reconstruction of Symmetric Objects by Fusing Visual and Tactile Sensing

Illonen, J., Bohg, J., Kyrki, V.

The International Journal of Robotics Research, 33(2):321-341, Sage, October 2013 (article)

Abstract
In this work, we propose to reconstruct a complete 3-D model of an unknown object by fusion of visual and tactile information while the object is grasped. Assuming the object is symmetric, a first hypothesis of its complete 3-D shape is generated. A grasp is executed on the object with a robotic manipulator equipped with tactile sensors. Given the detected contacts between the fingers and the object, the initial full object model including the symmetry parameters can be refined. This refined model will then allow the planning of more complex manipulation tasks. The main contribution of this work is an optimal estimation approach for the fusion of visual and tactile data applying the constraint of object symmetry. The fusion is formulated as a state estimation problem and solved with an iterative extended Kalman filter. The approach is validated experimentally using both artificial and real data from two different robotic platforms.

am

Web DOI Project Page [BibTex]

Web DOI Project Page [BibTex]


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Vibrotactile Display: Perception, Technology, and Applications

Choi, S., Kuchenbecker, K. J.

Proceedings of the IEEE, 101(9):2093-2104, sep 2013 (article)

hi

[BibTex]

[BibTex]


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ROS Open-source Audio Recognizer: ROAR Environmental Sound Detection Tools for Robot Programming

Romano, J. M., Brindza, J. P., Kuchenbecker, K. J.

Autonomous Robots, 34(3):207-215, April 2013 (article)

hi

[BibTex]

[BibTex]


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In Vivo Validation of a System for Haptic Feedback of Tool Vibrations in Robotic Surgery

Bark, K., McMahan, W., Remington, A., Gewirtz, J., Wedmid, A., Lee, D. I., Kuchenbecker, K. J.

Surgical Endoscopy, 27(2):656-664, February 2013, dynamic article (paper plus video), available at \href{http://www.springerlink.com/content/417j532708417342/}{http://www.springerlink.com/content/417j532708417342/} (article)

hi

[BibTex]

[BibTex]


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Perception of Springs with Visual and Proprioceptive Motion Cues: Implications for Prosthetics

Gurari, N., Kuchenbecker, K. J., Okamura, A. M.

IEEE Transactions on Human-Machine Systems, 43, pages: 102-114, January 2013, \href{http://www.youtube.com/watch?v=DBRw87Wk29E\&feature=youtu.be}{Video} (article)

hi

[BibTex]

[BibTex]


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Optimal control of reaching includes kinematic constraints

Mistry, M., Theodorou, E., Schaal, S., Kawato, M.

Journal of Neurophysiology, 2013, clmc (article)

Abstract
We investigate adaptation under a reaching task with an acceleration-based force field perturbation designed to alter the nominal straight hand trajectory in a potentially benign manner:pushing the hand of course in one direction before subsequently restoring towards the target. In this particular task, an explicit strategy to reduce motor effort requires a distinct deviation from the nominal rectilinear hand trajectory. Rather, our results display a clear directional preference during learning, as subjects adapted perturbed curved trajectories towards their initial baselines. We model this behavior using the framework of stochastic optimal control theory and an objective function that trades-of the discordant requirements of 1) target accuracy, 2) motor effort, and 3) desired trajectory. Our work addresses the underlying objective of a reaching movement, and we suggest that robustness, particularly against internal model uncertainly, is as essential to the reaching task as terminal accuracy and energy effciency.

am

PDF [BibTex]

PDF [BibTex]


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Expectation and Attention in Hierarchical Auditory Prediction

Chennu, S., Noreika, V., Gueorguiev, D., Blenkmann, A., Kochen, S., Ibáñez, A., Owen, A. M., Bekinschtein, T. A.

Journal of Neuroscience, 33(27):11194-11205, Society for Neuroscience, 2013 (article)

Abstract
Hierarchical predictive coding suggests that attention in humans emerges from increased precision in probabilistic inference, whereas expectation biases attention in favor of contextually anticipated stimuli. We test these notions within auditory perception by independently manipulating top-down expectation and attentional precision alongside bottom-up stimulus predictability. Our findings support an integrative interpretation of commonly observed electrophysiological signatures of neurodynamics, namely mismatch negativity (MMN), P300, and contingent negative variation (CNV), as manifestations along successive levels of predictive complexity. Early first-level processing indexed by the MMN was sensitive to stimulus predictability: here, attentional precision enhanced early responses, but explicit top-down expectation diminished it. This pattern was in contrast to later, second-level processing indexed by the P300: although sensitive to the degree of predictability, responses at this level were contingent on attentional engagement and in fact sharpened by top-down expectation. At the highest level, the drift of the CNV was a fine-grained marker of top-down expectation itself. Source reconstruction of high-density EEG, supported by intracranial recordings, implicated temporal and frontal regions differentially active at early and late levels. The cortical generators of the CNV suggested that it might be involved in facilitating the consolidation of context-salient stimuli into conscious perception. These results provide convergent empirical support to promising recent accounts of attention and expectation in predictive coding.

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

Ijspeert, A., Nakanishi, J., Pastor, P., Hoffmann, H., Schaal, S.

Neural Computation, (25):328-373, 2013, clmc (article)

Abstract
Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear systems is the focus of investigations, it is of equal importance to create goal-directed behavior (e.g., stable locomotion from a system of coupled oscillators under perceptual guidance). Modeling goal-directed behavior with nonlinear systems is, however, rather difficult due to the parameter sensitivity of these systems, their complex phase transitions in response to subtle parameter changes, and the difficulty of analyzing and predicting their long-term behavior; intuition and time-consuming parameter tuning play a major role. This letter presents and reviews dynamical movement primitives, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques. The essence of our approach is to start with a simple dynamical system, such as a set of linear differential equations, and transform those into a weakly nonlinear system with prescribed attractor dynamics by meansof a learnable autonomous forcing term. Both point attractors and limit cycle attractors of almost arbitrary complexity can be generated. We explain the design principle of our approach and evaluate its properties in several example applications in motor control and robotics.

am

link (url) [BibTex]

link (url) [BibTex]


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Modelling trial-by-trial changes in the mismatch negativity

Lieder, F., Daunizeau, J., Garrido, M. I., Friston, K. J., Stephan, K. E.

{PLoS} {C}omputational {B}iology, 9(2):e1002911, Public Library of Science, 2013 (article)

re

[BibTex]

[BibTex]


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A neurocomputational model of the mismatch negativity

Lieder, F., Stephan, K. E., Daunizeau, J., Garrido, M. I., Friston, K. J.

{PLoS Computational Biology}, 9(11):e1003288, Public Library of Science, 2013 (article)

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[BibTex]

[BibTex]


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Optimal distribution of contact forces with inverse-dynamics control

Righetti, L., Buchli, J., Mistry, M., Kalakrishnan, M., Schaal, S.

The International Journal of Robotics Research, 32(3):280-298, March 2013 (article)

Abstract
The development of legged robots for complex environments requires controllers that guarantee both high tracking performance and compliance with the environment. More specifically the control of the contact interaction with the environment is of crucial importance to ensure stable, robust and safe motions. In this contribution we develop an inverse-dynamics controller for floating-base robots under contact constraints that can minimize any combination of linear and quadratic costs in the contact constraints and the commands. Our main result is the exact analytical derivation of the controller. Such a result is particularly relevant for legged robots as it allows us to use torque redundancy to directly optimize contact interactions. For example, given a desired locomotion behavior, we can guarantee the minimization of contact forces to reduce slipping on difficult terrains while ensuring high tracking performance of the desired motion. The main advantages of the controller are its simplicity, computational efficiency and robustness to model inaccuracies. We present detailed experimental results on simulated humanoid and quadruped robots as well as a real quadruped robot. The experiments demonstrate that the controller can greatly improve the robustness of locomotion of the robots.1

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link (url) DOI [BibTex]

link (url) DOI [BibTex]

1999


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Is imitation learning the route to humanoid robots?

Schaal, S.

Trends in Cognitive Sciences, 3(6):233-242, 1999, clmc (article)

Abstract
This review will focus on two recent developments in artificial intelligence and neural computation: learning from imitation and the development of humanoid robots. It will be postulated that the study of imitation learning offers a promising route to gain new insights into mechanisms of perceptual motor control that could ultimately lead to the creation of autonomous humanoid robots. This hope is justified because imitation learning channels research efforts towards three important issues: efficient motor learning, the connection between action and perception, and modular motor control in form of movement primitives. In order to make these points, first, a brief review of imitation learning will be given from the view of psychology and neuroscience. In these fields, representations and functional connections between action and perception have been explored that contribute to the understanding of motor acts of other beings. The recent discovery that some areas in the primate brain are active during both movement perception and execution provided a first idea of the possible neural basis of imitation. Secondly, computational approaches to imitation learning will be described, initially from the perspective of traditional AI and robotics, and then with a focus on neural network models and statistical learning research. Parallels and differences between biological and computational approaches to imitation will be highlighted. The review will end with an overview of current projects that actually employ imitation learning for humanoid robots.

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link (url) [BibTex]

1999


link (url) [BibTex]


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Segmentation of endpoint trajectories does not imply segmented control

Sternad, D., Schaal, D.

Experimental Brain Research, 124(1):118-136, 1999, clmc (article)

Abstract
While it is generally assumed that complex movements consist of a sequence of simpler units, the quest to define these units of action, or movement primitives, still remains an open question. In this context, two hypotheses of movement segmentation of endpoint trajectories in 3D human drawing movements are re-examined: (1) the stroke-based segmentation hypothesis based on the results that the proportionality coefficient of the 2/3 power law changes discontinuously with each new â??strokeâ?, and (2) the segmentation hypothesis inferred from the observation of piecewise planar endpoint trajectories of 3D drawing movements. In two experiments human subjects performed a set of elliptical and figure-8 patterns of different sizes and orientations using their whole arm in 3D. The kinematic characteristics of the endpoint trajectories and the seven joint angles of the arm were analyzed. While the endpoint trajectories produced similar segmentation features as reported in the literature, analyses of the joint angles show no obvious segmentation but rather continuous oscillatory patterns. By approximating the joint angle data of human subjects with sinusoidal trajectories, and by implementing this model on a 7-degree-of-freedom anthropomorphic robot arm, it is shown that such a continuous movement strategy can produce exactly the same features as observed by the above segmentation hypotheses. The origin of this apparent segmentation of endpoint trajectories is traced back to the nonlinear transformations of the forward kinematics of human arms. The presented results demonstrate that principles of discrete movement generation may not be reconciled with those of rhythmic movement as easily as has been previously suggested, while the generalization of nonlinear pattern generators to arm movements can offer an interesting alternative to approach the question of units of action.

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link (url) [BibTex]

link (url) [BibTex]