Header logo is


2020


no image
Dynamic analysis of doubly curved composite panels using lamination parameters and spectral-Tchebychev method

Serhat, G., Anamagh, M. R., Bediz, B., Basdogan, I.

Computers & Structures, 239, pages: 106294, October 2020 (article)

Abstract
Efficient modeling and optimization techniques are required to overcome the high design complexity and computational costs concerning the engineering of composite structures. In this paper, a modeling framework for the dynamic analysis of doubly curved composite panels is developed. Lamination parameters are used to characterize the stiffness properties of the laminate, and the responses are calculated through the two-dimensional spectral-Tchebychev method. The proposed framework combines the computational efficiency advantages of both lamination parameters formulation and spectral-Tchebychev method which is extended for dynamic analysis of curved composite laminates. Compared to the finite element method, the developed model significantly decreases the computation duration, thereby leading to analysis speed-ups up to 40 folds. In the case studies, fundamental frequency contours for the doubly curved composite panels are obtained in lamination parameters space for the first time. The results show that, unlike flat or singly curved laminates, the maximum frequency design points for doubly curved panels can be inside the feasible region of lamination parameters requiring multiple layer angles. The fundamental mode shapes for the maximum frequency designs are also computed to investigate the influence of panel curvatures on the vibration patterns, which can exhibit mode switching phenomenon.

hi

DOI [BibTex]

2020


DOI [BibTex]


no image
Unifying Lamination Parameters with Spectral-Tchebychev Method for Variable-Stiffness Composite Plate Design

Serhat, G., Bediz, B., Basdogan, I.

Composite Structures, 242(112183), June 2020 (article)

Abstract
This paper describes an efficient framework for the design and optimization of the variable-stiffness composite plates. Equations of motion are solved using a Tchebychev polynomials-based spectral modeling approach that is extended for the classical laminated plate theory. This approach provides highly significant analysis speed-ups with respect to the conventional finite element method. The proposed framework builds on a variable-stiffness laminate design methodology that utilizes lamination parameters for representing the stiffness properties compactly and master node variables for modeling the stiffness variation through distance-based interpolation. The current study improves the existing method by optimizing the locations of the master nodes in addition to their lamination parameter values. The optimization process is promoted by the computationally efficient spectral-Tchebychev solution method. Case studies are performed for maximizing the fundamental frequencies of the plates with different boundary conditions and aspect ratios. The results show that significant improvements can be rapidly achieved compared to optimal constant-stiffness designs by utilizing the developed framework. In addition, the optimization of master node locations resulted in additional improvements in the optimal response values highlighting the importance of including the node positions within the design variables.

hi

DOI [BibTex]

DOI [BibTex]


no image
Automatic Discovery of Interpretable Planning Strategies

Skirzyński, J., Becker, F., Lieder, F.

May 2020 (article) Submitted

Abstract
When making decisions, people often overlook critical information or are overly swayed by irrelevant information. A common approach to mitigate these biases is to provide decisionmakers, especially professionals such as medical doctors, with decision aids, such as decision trees and flowcharts. Designing effective decision aids is a difficult problem. We propose that recently developed reinforcement learning methods for discovering clever heuristics for good decision-making can be partially leveraged to assist human experts in this design process. One of the biggest remaining obstacles to leveraging the aforementioned methods for improving human decision-making is that the policies they learn are opaque to people. To solve this problem, we introduce AI-Interpret: a general method for transforming idiosyncratic policies into simple and interpretable descriptions. Our algorithm combines recent advances in imitation learning and program induction with a new clustering method for identifying a large subset of demonstrations that can be accurately described by a simple, high-performing decision rule. We evaluate our new AI-Interpret algorithm and employ it to translate information-acquisition policies discovered through metalevel reinforcement learning. The results of three large behavioral experiments showed that the provision of decision rules as flowcharts significantly improved people’s planning strategies and decisions across three different classes of sequential decision problems. Furthermore, a series of ablation studies confirmed that our AI-Interpret algorithm was critical to the discovery of interpretable decision rules and that it is ready to be applied to other reinforcement learning problems. We conclude that the methods and findings presented in this article are an important step towards leveraging automatic strategy discovery to improve human decision-making.

re

Automatic Discovery of Interpretable Planning Strategies The code for our algorithm and the experiments is available [BibTex]


Physical Variables Underlying Tactile Stickiness during Fingerpad Detachment
Physical Variables Underlying Tactile Stickiness during Fingerpad Detachment

Nam, S., Vardar, Y., Gueorguiev, D., Kuchenbecker, K. J.

Frontiers in Neuroscience, 14(235):1-14, April 2020 (article)

Abstract
One may notice a relatively wide range of tactile sensations even when touching the same hard, flat surface in similar ways. Little is known about the reasons for this variability, so we decided to investigate how the perceptual intensity of light stickiness relates to the physical interaction between the skin and the surface. We conducted a psychophysical experiment in which nine participants actively pressed their finger on a flat glass plate with a normal force close to 1.5 N and detached it after a few seconds. A custom-designed apparatus recorded the contact force vector and the finger contact area during each interaction as well as pre- and post-trial finger moisture. After detaching their finger, participants judged the stickiness of the glass using a nine-point scale. We explored how sixteen physical variables derived from the recorded data correlate with each other and with the stickiness judgments of each participant. These analyses indicate that stickiness perception mainly depends on the pre-detachment pressing duration, the time taken for the finger to detach, and the impulse in the normal direction after the normal force changes sign; finger-surface adhesion seems to build with pressing time, causing a larger normal impulse during detachment and thus a more intense stickiness sensation. We additionally found a strong between-subjects correlation between maximum real contact area and peak pull-off force, as well as between finger moisture and impulse.

hi

link (url) DOI Project Page [BibTex]


no image
Advancing Rational Analysis to the Algorithmic Level

Lieder, F., Griffiths, T. L.

Behavioral and Brain Sciences, 43, E27, March 2020 (article)

Abstract
The commentaries raised questions about normativity, human rationality, cognitive architectures, cognitive constraints, and the scope or resource rational analysis (RRA). We respond to these questions and clarify that RRA is a methodological advance that extends the scope of rational modeling to understanding cognitive processes, why they differ between people, why they change over time, and how they could be improved.

re

Advancing rational analysis to the algorithmic level DOI [BibTex]

Advancing rational analysis to the algorithmic level DOI [BibTex]


no image
Learning to Overexert Cognitive Control in a Stroop Task

Bustamante, L., Lieder, F., Musslick, S., Shenhav, A., Cohen, J.

Febuary 2020, Laura Bustamante and Falk Lieder contributed equally to this publication. (article) In revision

Abstract
How do people learn when to allocate how much cognitive control to which task? According to the Learned Value of Control (LVOC) model, people learn to predict the value of alternative control allocations from features of a given situation. This suggests that people may generalize the value of control learned in one situation to other situations with shared features, even when the demands for cognitive control are different. This makes the intriguing prediction that what a person learned in one setting could, under some circumstances, cause them to misestimate the need for, and potentially over-exert control in another setting, even if this harms their performance. To test this prediction, we had participants perform a novel variant of the Stroop task in which, on each trial, they could choose to either name the color (more control-demanding) or read the word (more automatic). However only one of these tasks was rewarded, it changed from trial to trial, and could be predicted by one or more of the stimulus features (the color and/or the word). Participants first learned colors that predicted the rewarded task. Then they learned words that predicted the rewarded task. In the third part of the experiment, we tested how these learned feature associations transferred to novel stimuli with some overlapping features. The stimulus-task-reward associations were designed so that for certain combinations of stimuli the transfer of learned feature associations would incorrectly predict that more highly rewarded task would be color naming, which would require the exertion of control, even though the actually rewarded task was word reading and therefore did not require the engagement of control. Our results demonstrated that participants over-exerted control for these stimuli, providing support for the feature-based learning mechanism described by the LVOC model.

re

Learning to Overexert Cognitive Control in a Stroop Task DOI [BibTex]

Learning to Overexert Cognitive Control in a Stroop Task DOI [BibTex]


Learning to Predict Perceptual Distributions of Haptic Adjectives
Learning to Predict Perceptual Distributions of Haptic Adjectives

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

Frontiers in Neurorobotics, 13(116):1-16, Febuary 2020 (article)

Abstract
When humans touch an object with their fingertips, they can immediately describe its tactile properties using haptic adjectives, such as hardness and roughness; however, human perception is subjective and noisy, with significant variation across individuals and interactions. Recent research has worked to provide robots with similar haptic intelligence but was focused on identifying binary haptic adjectives, ignoring both attribute intensity and perceptual variability. Combining ordinal haptic adjective labels gathered from human subjects for a set of 60 objects with features automatically extracted from raw multi-modal tactile data collected by a robot repeatedly touching the same objects, we designed a machine-learning method that incorporates partial knowledge of the distribution of object labels into training; then, from a single interaction, it predicts a probability distribution over the set of ordinal labels. In addition to analyzing the collected labels (10 basic haptic adjectives) and demonstrating the quality of our method's predictions, we hold out specific features to determine the influence of individual sensor modalities on the predictive performance for each adjective. Our results demonstrate the feasibility of modeling both the intensity and the variation of haptic perception, two crucial yet previously neglected components of human haptic perception.

hi

DOI Project Page [BibTex]


no image
Exercising with Baxter: Preliminary Support for Assistive Social-Physical Human-Robot Interaction

Fitter, N. T., Mohan, M., Kuchenbecker, K. J., Johnson, M. J.

Journal of NeuroEngineering and Rehabilitation, 17(19), Febuary 2020 (article)

Abstract
Background: The worldwide population of older adults will soon exceed the capacity of assisted living facilities. Accordingly, we aim to understand whether appropriately designed robots could help older adults stay active at home. Methods: Building on related literature as well as guidance from experts in game design, rehabilitation, and physical and occupational therapy, we developed eight human-robot exercise games for the Baxter Research Robot, six of which involve physical human-robot contact. After extensive iteration, these games were tested in an exploratory user study including 20 younger adult and 20 older adult users. Results: Only socially and physically interactive games fell in the highest ranges for pleasantness, enjoyment, engagement, cognitive challenge, and energy level. Our games successfully spanned three different physical, cognitive, and temporal challenge levels. User trust and confidence in Baxter increased significantly between pre- and post-study assessments. Older adults experienced higher exercise, energy, and engagement levels than younger adults, and women rated the robot more highly than men on several survey questions. Conclusions: The results indicate that social-physical exercise with a robot is more pleasant, enjoyable, engaging, cognitively challenging, and energetic than similar interactions that lack physical touch. In addition to this main finding, researchers working in similar areas can build on our design practices, our open-source resources, and the age-group and gender differences that we found.

hi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Toward a Formal Theory of Proactivity
Toward a Formal Theory of Proactivity

Lieder, F., Iwama, G.

January 2020 (article) Submitted

Abstract
Beyond merely reacting to their environment and impulses, people have the remarkable capacity to proactively set and pursue their own goals. But the extent to which they leverage this capacity varies widely across people and situations. The goal of this article is to make the mechanisms and variability of proactivity more amenable to rigorous experiments and computational modeling. We proceed in three steps. First, we develop and validate a mathematically precise behavioral measure of proactivity and reactivity that can be applied across a wide range of experimental paradigms. Second, we propose a formal definition of proactivity and reactivity, and develop a computational model of proactivity in the AX Continuous Performance Task (AX-CPT). Third, we develop and test a computational-level theory of meta-control over proactivity in the AX-CPT that identifies three distinct meta-decision-making problems: intention setting, resolving response conflict between intentions and automaticity, and deciding whether to recall context and intentions into working memory. People's response frequencies in the AX-CPT were remarkably well captured by a mixture between the predictions of our models of proactive and reactive control. Empirical data from an experiment varying the incentives and contextual load of an AX-CPT confirmed the predictions of our meta-control model of individual differences in proactivity. Our results suggest that proactivity can be understood in terms of computational models of meta-control. Our model makes additional empirically testable predictions. Future work will extend our models from proactive control in the AX-CPT to proactive goal creation and goal pursuit in the real world.

re

Toward a formal theory of proactivity DOI Project Page [BibTex]


no image
Analytical classical density functionals from an equation learning network

Lin, S., Martius, G., Oettel, M.

The Journal of Chemical Physics, 152(2):021102, 2020, arXiv preprint \url{https://arxiv.org/abs/1910.12752} (article)

al

Preprint_PDF DOI [BibTex]

Preprint_PDF DOI [BibTex]

2016


no image
An electro-active polymer based lens module for dynamically varying focal system

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

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

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

hi

link (url) DOI [BibTex]

2016


link (url) DOI [BibTex]


no image
Wrinkle structures formed by formulating UV-crosslinkable liquid prepolymers

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

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

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

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
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]


no image
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]


no image
Structure modulated electrostatic deformable mirror for focus and geometry control

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

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

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

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
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]


no image
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]


no image
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]

2012


no image
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)

hi

[BibTex]

2012


[BibTex]


no image
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)

hi

[BibTex]

[BibTex]


Estimation of MIMO Closed-Loop Poles using Transfer Function Data
Estimation of MIMO Closed-Loop Poles using Transfer Function Data

Vardar, Y.

Eindhoven University of Technology, the Netherlands, 2012 (mastersthesis)

Abstract
For the development of high-tech systems such as lithographic positioning systems, throughput and accuracy are the main requirements. Nowadays, the trend to reach demanded accuracy and throughput levels is designing lightweight and consequently more flexible systems. To control these systems with a more effective and less conservative way, control design should go beyond the traditional rigid control and cope with the flexibilities that limit achievable bandwidth and performance. Therefore, conventional loop shaping methods are not sufficient to reach the performance criterions. Since obtaining an accurate parametric model is very complex and time-consuming for these high-tech systems, using well-developed model-based controller synthesis methods is also not a superior option. To achieve desired performance criterions, one solution can be implemented is reducing the gap between model-based and data-based control synthesis methods. In previous research, a method was developed to define the dynamic behavior of the system without a need for a parametric model. By this method transfer function data (TFD), which provides the information on the whole s-plane can be obtained from frequency response data (FRD) of the system. This innovation was a very important step to use data-based techniques for model-based controller synthesis methods. In this thesis firstly the standard technique to obtain TFD defined in [2] is extended. This standard technique to obtain TFD is not compatible with systems with pure integrators. To extend the methodology also for those systems, two techniques, which are altering the contour and filtering the system, are proposed. Then, the accuracy of TFD is investigated in detail. It is shown that the accuracy of TFD depends on the quality of FRD obtained and the computation techniques used to calculate TFD. Then, a technique which enables to determine the closed-loop poles of a MIMO system using TFD is discussed. The validity of the technique is proven with the help of complex function theory and calculus. Also, the factors that prevent determination of the closed-loop poles are discussed. In addition, it is observed that the accuracy of the closed-loop determination method depends on the quality of obtained TFD and the computation techniques. The proposed theory to obtain TFD and determination of closed-loop poles is validated with experiments conducted to a prototype lightweight system. Also, using experimental frequency response data of NXT-A7 test rig, the success of the proposed methodology is validated also for complex systems. Through these experimental results, it can be concluded that this new technique could be very advantageous in terms of ease of use and accuracy to determine the closed-loop poles of a MIMO lightly damped system.

hi

[BibTex]

[BibTex]


no image
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.

re

link (url) [BibTex]

link (url) [BibTex]


no image
Variants of guided self-organization for robot control

Martius, G., Herrmann, J.

Theory in Biosci., 131(3):129-137, Springer Berlin / Heidelberg, 2012 (article)

al

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
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]

2005


no image
Contact Location Display for Haptic Perception of Curvature and Object Motion

Provancher, W. R., Cutkosky, M. R., Kuchenbecker, K. J., Niemeyer, G.

International Journal of Robotics Research, 24(9):691-702, sep 2005 (article)

hi

[BibTex]

2005


[BibTex]


no image
Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers

Rolinek, M., Swoboda, P., Zietlow, D., Paulus, A., Musil, V., Martius, G.

Arxiv (article)

Abstract
Building on recent progress at the intersection of combinatorial optimization and deep learning, we propose an end-to-end trainable architecture for deep graph matching that contains unmodified combinatorial solvers. Using the presence of heavily optimized combinatorial solvers together with some improvements in architecture design, we advance state-of-the-art on deep graph matching benchmarks for keypoint correspondence. In addition, we highlight the conceptual advantages of incorporating solvers into deep learning architectures, such as the possibility of post-processing with a strong multi-graph matching solver or the indifference to changes in the training setting. Finally, we propose two new challenging experimental setups

al

Arxiv [BibTex]