Header logo is


2015


no image
Reducing Student Anonymity and Increasing Engagement

Kuchenbecker, K. J.

University of Pennsylvania Almanac, 62(18):8, November 2015 (article)

hi

[BibTex]

2015


[BibTex]


no image
Surgeons and Non-Surgeons Prefer Haptic Feedback of Instrument Vibrations During Robotic Surgery

Koehn, J. K., Kuchenbecker, K. J.

Surgical Endoscopy, 29(10):2970-2983, October 2015 (article)

hi

[BibTex]

[BibTex]


no image
Displaying Sensed Tactile Cues with a Fingertip Haptic Device

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

IEEE Transactions on Haptics, 8(4):384-396, October 2015 (article)

hi

[BibTex]

[BibTex]


no image
A thin film active-lens with translational control for dynamically programmable optical zoom

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

Applied Physics Letters, 107(8):081907, AIP Publishing, August 2015 (article)

Abstract
We demonstrate a thin film active-lens for rapidly and dynamically controllable optical zoom. The active-lens is composed of a convex hemispherical polydimethylsiloxane (PDMS) lens structure working as an aperture and a dielectric elastomer (DE) membrane actuator, which is a combination of a thin DE layer made with PDMS and a compliant electrode pattern using silver-nanowires. The active-lens is capable of dynamically changing focal point of the soft aperture as high as 18.4% through its translational movement in vertical direction responding to electrically induced bulged-up deformation of the DE membrane actuator. Under operation with various sinusoidal voltage signals, the movement responses are fairly consistent with those estimated from numerical simulation. The responses are not only fast, fairly reversible, and highly durable during continuous cyclic operations, but also large enough to impart dynamic focus tunability for optical zoom in microscopic imaging devices with a light-weight and ultra-slim configuration.

hi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Data-Driven Motion Mappings Improve Transparency in Teleoperation

Khurshid, R. P., Kuchenbecker, K. J.

Presence: Teleoperators and Virtual Environments, 24(2):132-154, May 2015 (article)

hi

[BibTex]

[BibTex]


no image
Robotic Learning of Haptic Adjectives Through Physical Interaction

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

Robotics and Autonomous Systems, 63(3):279-292, January 2015, Corrigendum published in June 2016 (article)

hi

[BibTex]

[BibTex]


no image
Effects of Vibrotactile Feedback on Human Motor Learning of Arbitrary Arm Motions

Bark, K., Hyman, E., Tan, F., Cha, E., Jax, S. A., Buxbaum, L. J., Kuchenbecker, K. J.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 23(1):51-63, January 2015 (article)

hi

[BibTex]

[BibTex]


no image
Probabilistic Interpretation of Linear Solvers

Hennig, P.

SIAM Journal on Optimization, 25(1):234-260, 2015 (article)

ei pn

Web PDF link (url) DOI [BibTex]

Web PDF link (url) DOI [BibTex]


no image
Probabilistic numerics and uncertainty in computations

Hennig, P., Osborne, M. A., Girolami, M.

Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 471(2179), 2015 (article)

Abstract
We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.

ei pn

PDF DOI [BibTex]

PDF DOI [BibTex]

2007


no image
Point-spread functions for backscattered imaging in the scanning electron microscope

Hennig, P., Denk, W.

Journal of Applied Physics , 102(12):1-8, December 2007 (article)

Abstract
One knows the imaging system's properties are central to the correct interpretation of any image. In a scanning electron microscope regions of different composition generally interact in a highly nonlinear way during signal generation. Using Monte Carlo simulations we found that in resin-embedded, heavy metal-stained biological specimens staining is sufficiently dilute to allow an approximately linear treatment. We then mapped point-spread functions for backscattered-electron contrast, for primary energies of 3 and 7 keV and for different detector specifications. The point-spread functions are surprisingly well confined (both laterally and in depth) compared even to the distribution of only those scattered electrons that leave the sample again.

ei pn

Web DOI [BibTex]

2007


Web DOI [BibTex]

2006


no image
Induced Master Motion in Force-Reflecting Teleoperation

Kuchenbecker, K. J., Niemeyer, G.

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

hi

[BibTex]

2006


[BibTex]


no image
Improving Contact Realism Through Event-Based Haptic Feedback

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

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

hi

[BibTex]

[BibTex]