MAGICTRAC, a novel method for conversion of whispering-gallery modes into a free-space Gaussian-like beam

1990 ◽  
Vol 11 (9) ◽  
pp. 1011-1032 ◽  
Author(s):  
B. W. Stallard ◽  
J. A. Byers ◽  
M. A. Makowski
2020 ◽  
Vol 28 (21) ◽  
pp. 31386
Author(s):  
Yong Yang ◽  
Xiaobei Zhang ◽  
Xiaochen Liu ◽  
Zijie Wang ◽  
Yang Yu ◽  
...  

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5950
Author(s):  
Alexey Ivanov ◽  
Kirill Min`kov ◽  
Alexey Samoilenko ◽  
Gennady Levin

A measurement system for the detection of a low concentration of nanoparticles based on optical microcavities with whispering-gallery modes (WGMs) is developed and investigated. A novel method based on the WGM broadening allows us to increase the precision of concentration measurements up to 0.005 ppm for nanoparticles of a known size. We describe WGM microcavity manufacturing and quality control methods. The collective interaction process of suspended Ag nanoparticles in a liquid and TiO2 in the air with a microcavity surface is studied.


2013 ◽  
Vol 21 (8) ◽  
pp. 9982 ◽  
Author(s):  
Chang-Ling Zou ◽  
Fang-Jie Shu ◽  
Fang-Wen Sun ◽  
Zhao-Jun Gong ◽  
Zheng-Fu Han ◽  
...  

2007 ◽  
Vol 32 (2-3) ◽  
pp. 123-126
Author(s):  
Y.-R. Nowicki-Bringuier ◽  
J. Claudon ◽  
C. Böckler ◽  
S. Reitzenstein ◽  
M. Kamp ◽  
...  

2021 ◽  
Author(s):  
Markku Suomalainen ◽  
Fares J. Abu-dakka ◽  
Ville Kyrki

AbstractWe present a novel method for learning from demonstration 6-D tasks that can be modeled as a sequence of linear motions and compliances. The focus of this paper is the learning of a single linear primitive, many of which can be sequenced to perform more complex tasks. The presented method learns from demonstrations how to take advantage of mechanical gradients in in-contact tasks, such as assembly, both for translations and rotations, without any prior information. The method assumes there exists a desired linear direction in 6-D which, if followed by the manipulator, leads the robot’s end-effector to the goal area shown in the demonstration, either in free space or by leveraging contact through compliance. First, demonstrations are gathered where the teacher explicitly shows the robot how the mechanical gradients can be used as guidance towards the goal. From the demonstrations, a set of directions is computed which would result in the observed motion at each timestep during a demonstration of a single primitive. By observing which direction is included in all these sets, we find a single desired direction which can reproduce the demonstrated motion. Finding the number of compliant axes and their directions in both rotation and translation is based on the assumption that in the presence of a desired direction of motion, all other observed motion is caused by the contact force of the environment, signalling the need for compliance. We evaluate the method on a KUKA LWR4+ robot with test setups imitating typical tasks where a human would use compliance to cope with positional uncertainty. Results show that the method can successfully learn and reproduce compliant motions by taking advantage of the geometry of the task, therefore reducing the need for localization accuracy.


Author(s):  
F. Bellarmine ◽  
Senthil Kumar Eswaran ◽  
Ramanjaneyulu Mannam ◽  
M. S. Ramachandra Rao

2020 ◽  
pp. 125599
Author(s):  
Pierluigi Amodio ◽  
Anton Arnold ◽  
Tatiana Levitina ◽  
Giuseppina Settanni ◽  
Ewa B. Weinmüller

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