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2019


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Limitations of the empirical Fisher approximation for natural gradient descent

Kunstner, F., Hennig, P., Balles, L.

Advances in Neural Information Processing Systems 32, pages: 4158-4169, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (conference)

ei pn

link (url) [BibTex]

2019


link (url) [BibTex]


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Convergence Guarantees for Adaptive Bayesian Quadrature Methods

Kanagawa, M., Hennig, P.

Advances in Neural Information Processing Systems 32, pages: 6234-6245, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (conference)

ei pn

link (url) [BibTex]

link (url) [BibTex]


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Deep Neural Network Approach in Electrical Impedance Tomography-Based Real-Time Soft Tactile Sensor

Park, H., Lee, H., Park, K., Mo, S., Kim, J.

In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 7447-7452, Macau, China, November 2019 (inproceedings)

Abstract
Recently, a whole-body tactile sensing have emerged in robotics for safe human-robot interaction. A key issue in the whole-body tactile sensing is ensuring large-area manufacturability and high durability. To fulfill these requirements, a reconstruction method called electrical impedance tomography (EIT) was adopted in large-area tactile sensing. This method maps voltage measurements to conductivity distribution using only a few number of measurement electrodes. A common approach for the mapping is using a linearized model derived from the Maxwell's equation. This linearized model shows fast computation time and moderate robustness against measurement noise but reconstruction accuracy is limited. In this paper, we propose a novel nonlinear EIT algorithm through Deep Neural Network (DNN) approach to improve the reconstruction accuracy of EIT-based tactile sensors. The neural network architecture with rectified linear unit (ReLU) function ensured extremely low computational time (0.002 seconds) and nonlinear network structure which provides superior measurement accuracy. The DNN model was trained with dataset synthesized in simulation environment. To achieve the robustness against measurement noise, the training proceeded with additive Gaussian noise that estimated through actual measurement noise. For real sensor application, the trained DNN model was transferred to a conductive fabric-based soft tactile sensor. For validation, the reconstruction error and noise robustness were mainly compared using conventional linearized model and proposed approach in simulation environment. As a demonstration, the tactile sensor equipped with the trained DNN model is presented for a contact force estimation.

hi

DOI [BibTex]

DOI [BibTex]


Effect of Remote Masking on Detection of Electrovibration
Effect of Remote Masking on Detection of Electrovibration

Jamalzadeh, M., Güçlü, B., Vardar, Y., Basdogan, C.

In Proceedings of the IEEE World Haptics Conference (WHC), pages: 229-234, Tokyo, Japan, July 2019 (inproceedings)

Abstract
Masking has been used to study human perception of tactile stimuli, including those created on haptic touch screens. Earlier studies have investigated the effect of in-site masking on tactile perception of electrovibration. In this study, we investigated whether it is possible to change detection threshold of electrovibration at fingertip of index finger via remote masking, i.e. by applying a (mechanical) vibrotactile stimulus on the proximal phalanx of the same finger. The masking stimuli were generated by a voice coil (Haptuator). For eight participants, we first measured the detection thresholds for electrovibration at the fingertip and for vibrotactile stimuli at the proximal phalanx. Then, the vibrations on the skin were measured at four different locations on the index finger of subjects to investigate how the mechanical masking stimulus propagated as the masking level was varied. Finally, electrovibration thresholds measured in the presence of vibrotactile masking stimuli. Our results show that vibrotactile masking stimuli generated sub-threshold vibrations around fingertip, and hence did not mechanically interfere with the electrovibration stimulus. However, there was a clear psychophysical masking effect due to central neural processes. Electrovibration absolute threshold increased approximately 0.19 dB for each dB increase in the masking level.

hi

DOI [BibTex]

DOI [BibTex]


Objective and Subjective Assessment of Algorithms for Reducing Three-Axis Vibrations to One-Axis Vibrations
Objective and Subjective Assessment of Algorithms for Reducing Three-Axis Vibrations to One-Axis Vibrations

Park, G., Kuchenbecker, K. J.

In Proceedings of the IEEE World Haptics Conference, pages: 467-472, July 2019 (inproceedings)

Abstract
A typical approach to creating realistic vibrotactile feedback is reducing 3D vibrations recorded by an accelerometer to 1D signals that can be played back on a haptic actuator, but some of the information is often lost in this dimensional reduction process. This paper describes seven representative algorithms and proposes four metrics based on the spectral match, the temporal match, and the average value and the variability of them across 3D rotations. These four performance metrics were applied to four texture recordings, and the method utilizing the discrete fourier transform (DFT) was found to be the best regardless of the sensing axis. We also recruited 16 participants to assess the perceptual similarity achieved by each algorithm in real time. We found the four metrics correlated well with the subjectively rated similarities for the six dimensional reduction algorithms, with the exception of taking the 3D vector magnitude, which was perceived to be good despite its low spectral and temporal match metrics.

hi

DOI [BibTex]

DOI [BibTex]


Fingertip Interaction Metrics Correlate with Visual and Haptic Perception of Real Surfaces
Fingertip Interaction Metrics Correlate with Visual and Haptic Perception of Real Surfaces

Vardar, Y., Wallraven, C., Kuchenbecker, K. J.

In Proceedings of the IEEE World Haptics Conference (WHC), pages: 395-400, Tokyo, Japan, July 2019 (inproceedings)

Abstract
Both vision and touch contribute to the perception of real surfaces. Although there have been many studies on the individual contributions of each sense, it is still unclear how each modality’s information is processed and integrated. To fill this gap, we investigated the similarity of visual and haptic perceptual spaces, as well as how well they each correlate with fingertip interaction metrics. Twenty participants interacted with ten different surfaces from the Penn Haptic Texture Toolkit by either looking at or touching them and judged their similarity in pairs. By analyzing the resulting similarity ratings using multi-dimensional scaling (MDS), we found that surfaces are similarly organized within the three-dimensional perceptual spaces of both modalities. Also, between-participant correlations were significantly higher in the haptic condition. In a separate experiment, we obtained the contact forces and accelerations acting on one finger interacting with each surface in a controlled way. We analyzed the collected fingertip interaction data in both the time and frequency domains. Our results suggest that the three perceptual dimensions for each modality can be represented by roughness/smoothness, hardness/softness, and friction, and that these dimensions can be estimated by surface vibration power, tap spectral centroid, and kinetic friction coefficient, respectively.

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design
Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design

Seifi, H., Fazlollahi, F., Oppermann, M., Sastrillo, J. A., Ip, J., Agrawal, A., Park, G., Kuchenbecker, K. J., MacLean, K. E.

In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Glasgow, Scotland, May 2019 (inproceedings)

Abstract
Creating haptic experiences often entails inventing, modifying, or selecting specialized hardware. However, experience designers are rarely engineers, and 30 years of haptic inventions are buried in a fragmented literature that describes devices mechanically rather than by potential purpose. We conceived of Haptipedia to unlock this trove of examples: Haptipedia presents a device corpus for exploration through metadata that matter to both device and experience designers. It is a taxonomy of device attributes that go beyond physical description to capture potential utility, applied to a growing database of 105 grounded force-feedback devices, and accessed through a public visualization that links utility to morphology. Haptipedia's design was driven by both systematic review of the haptic device literature and rich input from diverse haptic designers. We describe Haptipedia's reception (including hopes it will redefine device reporting standards) and our plans for its sustainability through community participation.

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Project Page [BibTex]

Project Page [BibTex]


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Internal Array Electrodes Improve the Spatial Resolution of Soft Tactile Sensors Based on Electrical Resistance Tomography

Lee, H., Park, K., Kim, J., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 5411-5417, Montreal, Canada, May 2019, Hyosang Lee and Kyungseo Park contributed equally to this publication (inproceedings)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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A Clustering Approach to Categorizing 7 Degree-of-Freedom Arm Motions during Activities of Daily Living

Gloumakov, Y., Spiers, A. J., Dollar, A. M.

In Proceedings of the International Conference on Robotics and Automation (ICRA), pages: 7214-7220, Montreal, Canada, May 2019 (inproceedings)

Abstract
In this paper we present a novel method of categorizing naturalistic human arm motions during activities of daily living using clustering techniques. While many current approaches attempt to define all arm motions using heuristic interpretation, or a combination of several abstract motion primitives, our unsupervised approach generates a hierarchical description of natural human motion with well recognized groups. Reliable recommendation of a subset of motions for task achievement is beneficial to various fields, such as robotic and semi-autonomous prosthetic device applications. The proposed method makes use of well-known techniques such as dynamic time warping (DTW) to obtain a divergence measure between motion segments, DTW barycenter averaging (DBA) to get a motion average, and Ward's distance criterion to build the hierarchical tree. The clusters that emerge summarize the variety of recorded motions into the following general tasks: reach-to-front, transfer-box, drinking from vessel, on-table motion, turning a key or door knob, and reach-to-back pocket. The clustering methodology is justified by comparing against an alternative measure of divergence using Bezier coefficients and K-medoids clustering.

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DOI [BibTex]

DOI [BibTex]


Improving Haptic Adjective Recognition with Unsupervised Feature Learning
Improving Haptic Adjective Recognition with Unsupervised Feature Learning

Richardson, B. A., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 3804-3810, Montreal, Canada, May 2019 (inproceedings)

Abstract
Humans can form an impression of how a new object feels simply by touching its surfaces with the densely innervated skin of the fingertips. Many haptics researchers have recently been working to endow robots with similar levels of haptic intelligence, but these efforts almost always employ hand-crafted features, which are brittle, and concrete tasks, such as object recognition. We applied unsupervised feature learning methods, specifically K-SVD and Spatio-Temporal Hierarchical Matching Pursuit (ST-HMP), to rich multi-modal haptic data from a diverse dataset. We then tested the learned features on 19 more abstract binary classification tasks that center on haptic adjectives such as smooth and squishy. The learned features proved superior to traditional hand-crafted features by a large margin, almost doubling the average F1 score across all adjectives. Additionally, particular exploratory procedures (EPs) and sensor channels were found to support perception of certain haptic adjectives, underlining the need for diverse interactions and multi-modal haptic data.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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DeepOBS: A Deep Learning Optimizer Benchmark Suite

Schneider, F., Balles, L., Hennig, P.

7th International Conference on Learning Representations (ICLR), May 2019 (conference)

ei pn

link (url) [BibTex]

link (url) [BibTex]


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Fast and Robust Shortest Paths on Manifolds Learned from Data

Arvanitidis, G., Hauberg, S., Hennig, P., Schober, M.

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1506-1515, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

ei pn

PDF link (url) [BibTex]

PDF link (url) [BibTex]


Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization
Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization

de Roos, F., Hennig, P.

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1448-1457, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

Abstract
Pre-conditioning is a well-known concept that can significantly improve the convergence of optimization algorithms. For noise-free problems, where good pre-conditioners are not known a priori, iterative linear algebra methods offer one way to efficiently construct them. For the stochastic optimization problems that dominate contemporary machine learning, however, this approach is not readily available. We propose an iterative algorithm inspired by classic iterative linear solvers that uses a probabilistic model to actively infer a pre-conditioner in situations where Hessian-projections can only be constructed with strong Gaussian noise. The algorithm is empirically demonstrated to efficiently construct effective pre-conditioners for stochastic gradient descent and its variants. Experiments on problems of comparably low dimensionality show improved convergence. In very high-dimensional problems, such as those encountered in deep learning, the pre-conditioner effectively becomes an automatic learning-rate adaptation scheme, which we also empirically show to work well.

ei pn

PDF link (url) [BibTex]

PDF link (url) [BibTex]


A Novel Texture Rendering Approach for Electrostatic Displays
A Novel Texture Rendering Approach for Electrostatic Displays

Fiedler, T., Vardar, Y.

In Proceedings of International Workshop on Haptic and Audio Interaction Design (HAID), Lille, France, March 2019 (inproceedings)

Abstract
Generating realistic texture feelings on tactile displays using data-driven methods has attracted a lot of interest in the last decade. However, the need for large data storages and transmission rates complicates the use of these methods for the future commercial displays. In this paper, we propose a new texture rendering approach which can compress the texture data signicantly for electrostatic displays. Using three sample surfaces, we first explain how to record, analyze and compress the texture data, and render them on a touchscreen. Then, through psychophysical experiments conducted with nineteen participants, we show that the textures can be reproduced by a signicantly less number of frequency components than the ones in the original signal without inducing perceptual degradation. Moreover, our results indicate that the possible degree of compression is affected by the surface properties.

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Fiedler19-HAID-Electrostatic [BibTex]

Fiedler19-HAID-Electrostatic [BibTex]

2016


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Qualitative User Reactions to a Hand-Clapping Humanoid Robot

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

In Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings, 9979, pages: 317-327, Lecture Notes in Artificial Intelligence, Springer International Publishing, November 2016, Oral presentation given by Fitter (inproceedings)

hi

[BibTex]

2016


[BibTex]


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Designing and Assessing Expressive Open-Source Faces for the Baxter Robot

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

In Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings, 9979, pages: 340-350, Lecture Notes in Artificial Intelligence, Springer International Publishing, November 2016, Oral presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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Rhythmic Timing in Playful Human-Robot Social Motor Coordination

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

In Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings, 9979, pages: 296-305, Lecture Notes in Artificial Intelligence, Springer International Publishing, November 2016, Oral presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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Using IMU Data to Demonstrate Hand-Clapping Games to a Robot

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

In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 851 - 856, October 2016, Interactive presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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ProtonPack: A Visuo-Haptic Data Acquisition System for Robotic Learning of Surface Properties

Burka, A., Hu, S., Helgeson, S., Krishnan, S., Gao, Y., Hendricks, L. A., Darrell, T., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pages: 58-65, 2016, Oral presentation given by Burka (inproceedings)

hi

Project Page [BibTex]

Project Page [BibTex]


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Equipping the Baxter Robot with Human-Inspired Hand-Clapping Skills

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

In Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pages: 105-112, 2016 (inproceedings)

hi

[BibTex]

[BibTex]


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Comparison of vibro-acoustic performance metrics in the design and optimization of stiffened composite fuselages

Serhat, G., Basdogan, I.

In Proceedings of International Congress and Exposition of Noise Control Engineering (INTER-NOISE), Hamburg, Germany, August 2016 (inproceedings)

Abstract
In this paper, a comparison of preliminary design methodologies for optimization of stiffened, fiber-reinforced composite fuselages for vibro-acoustic requirements is presented. Fuselage stiffness properties are modelled using lamination parameters and their effect on the vibro-acoustic performance is investigated using two different approaches. First method, only considers the structural model in order to explore the effect of design variables on fuselage vibrations. The simplified estimation of the acoustic behavior without considering fluid-structure interaction brings certain advantages such as reduced modelling effort and computational cost. In this case, the performance metric is chosen as equivalent radiated power (ERP) which is a well-known criterion in the prediction of structure-born noise. Second method, utilizes coupled vibro-acoustic models to predict the sound pressure levels (SPL) inside the fuselage. ERP is calculated both for bay panels and fuselage section and then compared with the SPL results. The response surfaces of each metric are determined as a function of lamination parameters and their overall difference is quantified. ERP approach proves its merit provided that a sufficiently accurate model is used. The results demonstrate the importance of the simplifications made in the modelling and the selection of analysis approach in vibro-acoustic design of fuselages.

hi

[BibTex]

[BibTex]


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Reproducing a Laser Pointer Dot on a Secondary Projected Screen

Hu, S., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pages: 1645-1650, 2016, Oral presentation given by Hu (inproceedings)

hi

[BibTex]

[BibTex]


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Effect of Aspect Ratio and Boundary Conditions on the Eigenfrequency Optimization of Composite Panels Using Lamination Parameters

Serhat, G., Basdogan, I.

In Proceedings of the ASMO UK International Conference on Numerical Optimisation Methods for Engineering Design, pages: 160–168, Munich, Germany, July 2016 (inproceedings)

Abstract
Eigenfrequency optimization of laminated composite panels is a common engineering problem. This process mostly involves designing stiffness properties of the structure. Optimal results can differ significantly depending on the values of the model parameters and the metrics used for the optimization. Building the know-how on this matter is crucial for choosing the appropriate design methodologies as well as validation and justification of prospective results. In this paper, effects of aspect ratio and boundary conditions on eigenfrequency optimization of composite panels by altering stiffness properties are investigated. Lamination parameters are chosen as design variables which are used in the modeling of stiffness tensors. This technique enables representation of overall stiffness characteristics and provides a convex design space. Fundamental frequency and difference between fundamental and second natural frequencies are maximized as design objectives. Optimization studies incorporating different models and responses are performed. Optimal lamination parameters and response values are provided for each case and the effects of model parameters on the solutions are quantified. The results indicate that trends of the optima change for different aspect ratio ranges and boundary conditions. Moreover, convergence occurs beyond certain critical values of the model parameters which may cause an optimization study to be redundant.

hi

[BibTex]

[BibTex]


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Multi-objective optimization of stiffened, fiber-reinforced composite fuselages for mechanical and vibro-acoustic requirements

Serhat, G., Faria, T. G., Basdogan, I.

In Proceedings of AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Washington, USA, June 2016 (inproceedings)

Abstract
In this paper, a preliminary design methodology for optimization of stiffened, fiber-reinforced composite fuselages for combined mechanical and vibro-acoustic requirements is presented. Laminate stiffness distributions are represented using the method called lamination parameters which is known to provide a convex solution space. Single-objective and multi-objective optimization studies are carried out in order to find optimal stiffness distributions. Performance metrics for acoustical behavior are chosen as maximum fundamental frequency and minimum equivalent radiated power. The mechanical performance metric is chosen as the maximum stiffness. The results show that the presented methodology works effectively and it can be used to improve load-carrying and acoustical performances simultaneously.

hi

DOI [BibTex]

DOI [BibTex]


Active Uncertainty Calibration in Bayesian ODE Solvers
Active Uncertainty Calibration in Bayesian ODE Solvers

Kersting, H., Hennig, P.

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 309-318, (Editors: Ihler, A. and Janzing, D.), AUAI Press, June 2016 (conference)

Abstract
There is resurging interest, in statistics and machine learning, in solvers for ordinary differential equations (ODEs) that return probability measures instead of point estimates. Recently, Conrad et al.~introduced a sampling-based class of methods that are `well-calibrated' in a specific sense. But the computational cost of these methods is significantly above that of classic methods. On the other hand, Schober et al.~pointed out a precise connection between classic Runge-Kutta ODE solvers and Gaussian filters, which gives only a rough probabilistic calibration, but at negligible cost overhead. By formulating the solution of ODEs as approximate inference in linear Gaussian SDEs, we investigate a range of probabilistic ODE solvers, that bridge the trade-off between computational cost and probabilistic calibration, and identify the inaccurate gradient measurement as the crucial source of uncertainty. We propose the novel filtering-based method Bayesian Quadrature filtering (BQF) which uses Bayesian quadrature to actively learn the imprecision in the gradient measurement by collecting multiple gradient evaluations.

ei pn

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


Automatic LQR Tuning Based on Gaussian Process Global Optimization
Automatic LQR Tuning Based on Gaussian Process Global Optimization

Marco, A., Hennig, P., Bohg, J., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 270-277, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

Abstract
This paper proposes an automatic controller tuning framework based on linear optimal control combined with Bayesian optimization. With this framework, an initial set of controller gains is automatically improved according to a pre-defined performance objective evaluated from experimental data. The underlying Bayesian optimization algorithm is Entropy Search, which represents the latent objective as a Gaussian process and constructs an explicit belief over the location of the objective minimum. This is used to maximize the information gain from each experimental evaluation. Thus, this framework shall yield improved controllers with fewer evaluations compared to alternative approaches. A seven-degree- of-freedom robot arm balancing an inverted pole is used as the experimental demonstrator. Results of a two- and four- dimensional tuning problems highlight the method’s potential for automatic controller tuning on robotic platforms.

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Video - Automatic LQR Tuning Based on Gaussian Process Global Optimization - ICRA 2016 Video - Automatic Controller Tuning on a Two-legged Robot PDF DOI Project Page [BibTex]

Video - Automatic LQR Tuning Based on Gaussian Process Global Optimization - ICRA 2016 Video - Automatic Controller Tuning on a Two-legged Robot PDF DOI Project Page [BibTex]


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Batch Bayesian Optimization via Local Penalization

González, J., Dai, Z., Hennig, P., Lawrence, N.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 648-657, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C.), May 2016 (conference)

ei pn

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Probabilistic Approximate Least-Squares
Probabilistic Approximate Least-Squares

Bartels, S., Hennig, P.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 676-684, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C. ), May 2016 (conference)

Abstract
Least-squares and kernel-ridge / Gaussian process regression are among the foundational algorithms of statistics and machine learning. Famously, the worst-case cost of exact nonparametric regression grows cubically with the data-set size; but a growing number of approximations have been developed that estimate good solutions at lower cost. These algorithms typically return point estimators, without measures of uncertainty. Leveraging recent results casting elementary linear algebra operations as probabilistic inference, we propose a new approximate method for nonparametric least-squares that affords a probabilistic uncertainty estimate over the error between the approximate and exact least-squares solution (this is not the same as the posterior variance of the associated Gaussian process regressor). This allows estimating the error of the least-squares solution on a subset of the data relative to the full-data solution. The uncertainty can be used to control the computational effort invested in the approximation. Our algorithm has linear cost in the data-set size, and a simple formal form, so that it can be implemented with a few lines of code in programming languages with linear algebra functionality.

ei pn

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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Deep Learning for Tactile Understanding From Visual and Haptic Data

Gao, Y., Hendricks, L. A., Kuchenbecker, K. J., Darrell, T.

In Proceedings of the IEEE International Conference on Robotics and Automation, pages: 536-543, May 2016, Oral presentation given by Gao (inproceedings)

hi

[BibTex]

[BibTex]


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Robust Tactile Perception of Artificial Tumors Using Pairwise Comparisons of Sensor Array Readings

Hui, J. C. T., Block, A. E., Taylor, C. J., Kuchenbecker, K. J.

In Proceedings of the IEEE Haptics Symposium, pages: 305-312, Philadelphia, Pennsylvania, USA, April 2016, Oral presentation given by Hui (inproceedings)

hi

[BibTex]

[BibTex]


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Data-Driven Comparison of Four Cutaneous Displays for Pinching Palpation in Robotic Surgery

Brown, J. D., Ibrahim, M., Chase, E. D. Z., Pacchierotti, C., Kuchenbecker, K. J.

In Proceedings of the IEEE Haptics Symposium, pages: 147-154, Philadelphia, Pennsylvania, USA, April 2016, Oral presentation given by Brown (inproceedings)

hi

[BibTex]

[BibTex]


Multisensory Robotic Therapy through Motion Capture and Imitation for Children with ASD
Multisensory Robotic Therapy through Motion Capture and Imitation for Children with ASD

Burns, R., Nizambad, S., Park, C. H., Jeon, M., Howard, A.

Proceedings of the American Society of Engineering Education, Mid-Atlantic Section, Spring Conference, April 2016 (conference)

Abstract
It is known that children with autism have difficulty with emotional communication. As the population of children with autism increases, it is crucial we create effective therapeutic programs that will improve their communication skills. We present an interactive robotic system that delivers emotional and social behaviors for multi­sensory therapy for children with autism spectrum disorders. Our framework includes emotion­-based robotic gestures and facial expressions, as well as tracking and understanding the child’s responses through Kinect motion capture.

hi

link (url) [BibTex]

link (url) [BibTex]


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Design and Implementation of a Visuo-Haptic Data Acquisition System for Robotic Learning of Surface Properties

Burka, A., Hu, S., Helgeson, S., Krishnan, S., Gao, Y., Hendricks, L. A., Darrell, T., Kuchenbecker, K. J.

In Proceedings of the IEEE Haptics Symposium, pages: 350-352, April 2016, Work-in-progress paper. Poster presentation given by Burka (inproceedings)

hi

Project Page [BibTex]

Project Page [BibTex]


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Psychophysical Power Optimization of Friction Modulation for Tactile Interfaces

Sednaoui, T., Vezzoli, E., Gueorguiev, D., Amberg, M., Chappaz, C., Lemaire-Semail, B.

In Haptics: Perception, Devices, Control, and Applications, pages: 354-362, Springer International Publishing, Cham, 2016 (inproceedings)

Abstract
Ultrasonic vibration and electrovibration can modulate the friction between a surface and a sliding finger. The power consumption of these devices is critical to their integration in modern mobile devices such as smartphones. This paper presents a simple control solution to reduce up to 68.8 {\%} this power consumption by taking advantage of the human perception limits.

hi

[BibTex]

[BibTex]


Effect of Waveform in Haptic Perception of Electrovibration on Touchscreens
Effect of Waveform in Haptic Perception of Electrovibration on Touchscreens

Vardar, Y., Güçlü, B., Basdogan, C.

In Haptics: Perception, Devices, Control, and Applications, pages: 190-203, Springer International Publishing, Cham, 2016 (inproceedings)

Abstract
The perceived intensity of electrovibration can be altered by modulating the amplitude, frequency, and waveform of the input voltage signal applied to the conductive layer of a touchscreen. Even though the effect of the first two has been already investigated for sinusoidal signals, we are not aware of any detailed study investigating the effect of the waveform on our haptic perception in the domain of electrovibration. This paper investigates how input voltage waveform affects our haptic perception of electrovibration on touchscreens. We conducted absolute detection experiments using square wave and sinusoidal input signals at seven fundamental frequencies (15, 30, 60, 120, 240, 480 and 1920 Hz). Experimental results depicted the well-known U-shaped tactile sensitivity across frequencies. However, the sensory thresholds were lower for the square wave than the sinusoidal wave at fundamental frequencies less than 60 Hz while they were similar at higher frequencies. Using an equivalent circuit model of a finger-touchscreen system, we show that the sensation difference between the waveforms at low fundamental frequencies can be explained by frequency-dependent electrical properties of human skin and the differential sensitivity of mechanoreceptor channels to individual frequency components in the electrostatic force. As a matter of fact, when the electrostatic force waveforms are analyzed in the frequency domain based on human vibrotactile sensitivity data from the literature [15], the electrovibration stimuli caused by square-wave input signals at all the tested frequencies in this study are found to be detected by the Pacinian psychophysical channel.

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vardar_eurohaptics_2016 [BibTex]

vardar_eurohaptics_2016 [BibTex]

2013


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Virtual Robotization of the Human Body via Data-Driven Vibrotactile Feedback

Kurihara, Y., Hachisu, T., Kuchenbecker, K. J., Kajimoto, H.

In Proc. International Conference on Advances in Computer Entertainment Technology (ACE), 8253, pages: 109-122, Lecture Notes in Computer Science, Springer, Enschede, Netherlands, 2013, Oral presentation given by Kurihara. Best Paper Silver Award (inproceedings)

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[BibTex]

2013


[BibTex]


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Governance of Humanoid Robot Using Master Exoskeleton

Kumra, S., Mohan, M., Gupta, S., Vaswani, H.

In Proceedings of the IEEE International Symposium on Robotics (ISR), Seoul, South Korea, October 2013 (inproceedings)

Abstract
Dexto:Eka: is an adult-size humanoid robot being developed with the aim of achieving tele-presence. The paper sheds light on the control of this robot using a Master Exoskeleton which comprises of an Exo-Frame, a Control Column and a Graphical User Interface. It further illuminates the processes and algorithms that have been utilized to make an efficient system that would effectively emulate a tele-operator.

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DOI [BibTex]

DOI [BibTex]


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Virtual Robotization of the Human Body Using Vibration Recording, Modeling and Rendering

Kurihara, Y., Hachisu, T., Kuchenbecker, K. J., Kajimoto, H.

In Proc. Virtual Reality Society of Japan Annual Conference, Osaka, Japan, sep 2013, Paper written in Japanese. Presentation given by Kurihara (inproceedings)

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[BibTex]

[BibTex]


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Design and development part 2 of Dexto:Eka: - The humanoid robot

Kumra, S., Mohan, M., Gupta, S., Vaswani, H.

In Proceedings of the International Conference on Mechatronics and Automation (ICMA), Takamatsu, Japan, August 2013 (inproceedings)

Abstract
Through this paper, we elucidate the second phase of the design and development of the tele-operated humanoid robot Dexto:Eka:. Phase one comprised of the development of a 6 DoF left anthropomorphic arm and left exo-frame. Here, we illustrate the development of the right arm, right exo-frame, torso, backbone, human machine interface and omni-directional locomotion system. Dexto:Eka: will be able to communicate with a remote user through Wi-Fi. An exo-frame capacitates it to emulate human arms and its locomotion is controlled by joystick. A Graphical User Interface monitors and helps in controlling the system.

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DOI [BibTex]

DOI [BibTex]


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Virtual Alteration of Body Material by Reality-Based Periodic Vibrotactile Feedback

Kurihara, Y., Hachisu, T., Sato, M., Fukushima, S., Kuchenbecker, K. J., Kajimoto, H.

In Proc. JSME Robotics and Mechatronics Conference (ROBOMEC), Tsukuba, Japan, May 2013, Paper written in Japanese. Poster presentation given by {Kurihara} (inproceedings)

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[BibTex]

[BibTex]


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The Design and Field Observation of a Haptic Notification System for Oral Presentations

Tam, D., MacLean, K. E., McGrenere, J., Kuchenbecker, K. J.

In Proc. SIGCHI Conference on Human Factors in Computing Systems, pages: 1689-1698, Paris, France, May 2013, Oral presentation given by Tam (inproceedings)

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[BibTex]

[BibTex]


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Using Robotic Exploratory Procedures to Learn the Meaning of Haptic Adjectives

Chu, V., McMahon, I., Riano, L., McDonald, C. G., He, Q., Perez-Tejada, J. M., Arrigo, M., Fitter, N., Nappo, J., Darrell, T., Kuchenbecker, K. J.

In Proc. IEEE International Conference on Robotics and Automation, pages: 3048-3055, Karlsruhe, Germany, May 2013, Oral presentation given by Chu. Best Cognitive Robotics Paper Award (inproceedings)

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[BibTex]

[BibTex]


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Instrument contact vibrations are a construct-valid measure of technical skill in Fundamentals of Laparoscopic Surgery Training Tasks

Gomez, E. D., Aggarwal, R., McMahan, W., Koch, E., Hashimoto, D. A., Darzi, A., Murayama, K. M., Dumon, K. R., Williams, N. N., Kuchenbecker, K. J.

In Proc. Annual Meeting of the Association for Surgical Education, Orlando, Florida, USA, 2013, Oral presentation given by Gomez (inproceedings)

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[BibTex]

[BibTex]


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Dynamic Simulation of Tool-Mediated Texture Interaction

McDonald, C. G., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, pages: 307-312, Daejeon, South Korea, April 2013, Oral presentation given by McDonald (inproceedings)

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[BibTex]

[BibTex]


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Generating Haptic Texture Models From Unconstrained Tool-Surface Interactions

Culbertson, H., Unwin, J., Goodman, B. E., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, pages: 295-300, Daejeon, South Korea, April 2013, Oral presentation given by Culbertson. Finalist for Best Paper Award (inproceedings)

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[BibTex]

[BibTex]


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A practical System for Recording Instrument Contacts and Collisions During Transoral Robotic Surgery

Gomez, E. D., Weinstein, G. S., O’Malley, J. B. W., McMahan, W., Chen, L., Kuchenbecker, K. J.

In Proc. Annual Meeting of the Triological Society, Orlando, Florida, USA, April 2013, Poster presentation given by Gomez (inproceedings)

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[BibTex]

[BibTex]


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The Randomized Dependence Coefficient

Lopez-Paz, D., Hennig, P., Schölkopf, B.

In Advances in Neural Information Processing Systems 26, pages: 1-9, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

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PDF [BibTex]

PDF [BibTex]


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Fast Probabilistic Optimization from Noisy Gradients

Hennig, P.

In Proceedings of The 30th International Conference on Machine Learning, JMLR W&CP 28(1), pages: 62–70, (Editors: S Dasgupta and D McAllester), ICML, 2013 (inproceedings)

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PDF [BibTex]

PDF [BibTex]


Nonparametric dynamics estimation for time periodic systems
Nonparametric dynamics estimation for time periodic systems

Klenske, E., Zeilinger, M., Schölkopf, B., Hennig, P.

In Proceedings of the 51st Annual Allerton Conference on Communication, Control, and Computing, pages: 486-493 , 2013 (inproceedings)

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PDF DOI [BibTex]

PDF DOI [BibTex]