1,134 research outputs found
Singularity Avoidance for Cart-Mounted Hand-Guided Collaborative Robots: A Variational Approach
Most collaborative robots (cobots) can be taught by hand guiding: essentially, by manually jogging the robot, an operator teaches some configurations to be employed as via points. Based on those via points, Cartesian end-effector trajectories such as straight lines, circular arcs or splines are then constructed. Such methods can, in principle, be employed for cart-mounted cobots (i.e., when the jogging involves one or two linear axes, besides the cobot axes). However, in some applications, the sole imposition of via points in Cartesian space is not sufficient. On the contrary, albeit the overall system is redundant, (i) the via points must be reached at the taught joint configurations, and (ii) the undesirable singularity (and near-singularity) conditions must be avoided. The naive approach, consisting of setting the cart trajectory beforehand (for instance, by imposing a linear-in-time motion law that crosses the taught cart configurations), satisfies the first need, but does not guarantee the satisfaction of the second. Here, we propose an approach consisting of (i) a novel strategy for decoupling the planning of the cart trajectory and that of the robot joints, and (ii) a novel variational technique for computing the former in a singularity-aware fashion, ensuring the avoidance of a class of workspace singularity and near-singularity configurations
Closed-loop Control from Data-Driven Open-Loop Optimal Control Trajectories
We show how the recent works on data driven open-loop minimum-energy control for linear systems can be exploited to obtain closed-loop piecewise-affine control laws, by employing a state-space partitioning technique which is at the basis of the static relatively optimal control. In addition, we propose a way for employing portions of the experimental input and state trajectories to recover information about the natural movement of the state and dealing with non-zero initial conditions. The same idea can be used for formulating several open-loop control problems entirely based on data, possibly including input and state constraints
Star-forming galaxies versus low- and high-excitation radio AGN in the VLA-COSMOS 3GHz Large Project
We study the composition of the faint radio population selected from the
VLA-COSMOS 3GHz Large Project, a radio continuum survey performed at 10 cm
wavelength. The survey covers the full 2 square degree COSMOS field with mean
Jy/beam, cataloging 10,899 source components above . By combining these radio data with UltraVISTA, optical, near-infrared,
and Spitzer/IRAC mid-infrared data, as well as X-ray data from the Chandra
Legacy, and Chandra COSMOS surveys, we gain insight into the emission
mechanisms within our radio sources out to redshifts of . From these
emission characteristics we classify our souces as star forming galaxies or
AGN. Using their multi-wavelength properties we further separate the AGN into
sub-samples dominated by radiatively efficient and inefficient AGN, often
referred to as high- and low-excitation emission line AGN. We compare our
method with other results based on fitting of the sources' spectral energy
distributions using both galaxy and AGN spectral models, and those based on the
infrared-radio correlation. We study the fractional contributions of these
sub-populations down to radio flux levels of 10 Jy. We find that at
3 GHz flux densities above 400 Jy quiescent, red galaxies,
consistent with the low-excitation radio AGN class constitute the dominant
fraction. Below densities of 200 Jy star-forming galaxies begin to
constitute the largest fraction, followed by the low-excitation, and X-ray- and
IR-identified high-excitation radio AGN.Comment: 7 pages, 3 figures, The many facets of extragalactic radio surveys:
towards new scientific challenges, Bologna 20-23 October 201
Recommended from our members
Dynamic neural network architectures for on field stochastic calibration of indicative low cost air quality sensing systems
In the last few years, the interest in the development of new pervasive or mobile implementations of air quality multisensor devices has significantly grown. New application opportunities appeared together with new challenges due to limitations in dealing with rapid pollutants concentrations transients both for static and mobile deployments. In this work, we propose a Dynamic Neural Network (DNN) approach to the stochastic prediction of air pollutants concentrations by means of chemical multisensor devices. DNN architectures have been devised and tested in order to tackle the cross sensitivities issues and sensors inherent dynamic limitations. Testing have been performed using an on-field recorded dataset from a pervasive deployment in Cambridge (UK), encompassing several weeks. The results obtained with the dynamic model are compared with the response of the static neural network and the performance analysis indicates the capability of the on-field dynamic multivariate calibration to ameliorate the static calibration approach performance in this real world air quality monitoring scenario. Interestingly, results analysis also suggests that the improvements are more significant when pollutants concentration changes more rapidly.This work has been supported by an STSM (Short Term Scientific Mission) grant from COST Action TD1105 EuNetAir
Faint AGNs at z>4 in the CANDELS GOODS-S field: looking for contributors to the reionization of the Universe
In order to derive the AGN contribution to the cosmological ionizing
emissivity we have selected faint AGN candidates at in the CANDELS
GOODS-South field which is one of the deepest fields with extensive
multiwavelength coverage from Chandra, HST, Spitzer and various groundbased
telescopes. We have adopted a relatively novel criterion. As a first step high
redshift galaxies are selected in the NIR band down to very faint levels
() using reliable photometric redshifts. This corresponds at to
a selection criterion based on the galaxy rest-frame UV flux. AGN candidates
are then picked up from this parent sample if they show X-ray fluxes above a
threshold of cgs (0.5-2 keV). We have found 22 AGN
candidates at and we have derived the first estimate of the UV luminosity
function in the redshift interval and absolute magnitude interval
typical of local Seyfert galaxies. The
faint end of the derived luminosity function is about two/four magnitudes
fainter at than that derived from previous UV surveys. We have then
estimated ionizing emissivities and hydrogen photoionization rates in the same
redshift interval under reasonable assumptions and after discussion of possible
caveats, the most important being the large uncertainties involved in the
estimate of photometric redshift for sources with featureless, almost power-law
SEDs and/or low average escape fraction of ionizing photons from the AGN host
galaxies. We argue that, under reasonable evaluations of possible biases, the
probed AGN population can produce at photoionization rates consistent
with that required to keep highly ionized the intergalactic medium observed in
the Lyman- forest of high redshift QSO spectra, providing an important
contribution to the cosmic reionization.Comment: 15 pages, 8 figures, A&A accepted, updated figure 6, corrected typo
in table 3, updated reference
Type 2 Quasars at the heart of dust-obscured galaxies (DOGs) at high z
Dust‐obscured galaxies (DOGs) represent a recently‐discovered, intriguing class of mid‐IR luminous sources at high redshifts. Evidence is mounting that DOGs (selected on the basis of extreme optical/mid‐IR color cut and high mid‐IR flux level) may represent systems caught in the process of host galaxy formation and intense SMBH growth. Here we report the results of an X‐ray spectroscopic survey aimed at studying the X‐ray properties of these sources and establishing the fraction of Type 2 quasars among them
High-z X-ray Obscured Quasars in Galaxies with Extreme Mid-IR/Optical Colors
Extreme Optical/Mid‐IR color cuts have been used to uncover a population of dust‐enshrouded, mid‐IR luminous galaxies at high redshifts. Several lines of evidence point towards the presence of an heavily absorbed, possibly Compton‐thick quasar at the heart of these systems. Nonetheless, the X‐ray spectral properties of these intriguing sources still remain largely unexplored. Here we present an X‐ray spectroscopic study of a large sample of 44 extreme dust‐obscured galaxies (EDOGs) with F_(24μm)/F_R > 2000 and F_(24μm) > 1.3 mJy selected from a 6 deg^2 region in the SWIRE fields. The application of our selection criteria to a wide area survey has been capable of unveiling a population of X‐ray luminous, absorbed z > 1 quasars which is mostly missed in the traditional optical/X‐ray surveys performed so far. Advances in the understanding of the X‐ray properties of these recently‐discovered sources by Simbol‐X observations will be also discussed
The 2-10 keV unabsorbed luminosity function of AGN from the XMM-Newton LSS, CDFS and COSMOS surveys
The XMM-LSS, XMM-COSMOS, and XMM-CDFS surveys are complementary in terms of
sky coverage and depth. Together, they form a clean sample with the least
possible variance in instrument effective areas and PSF. Therefore this is one
of the best samples available to determine the 2-10 keV luminosity function of
AGN and its evolution. The samples and the relevant corrections for
incompleteness are described. A total of 2887 AGN is used to build the LF in
the luminosity interval 10^42-10^46 erg/s, and in the redshift interval
0.001-4. A new method to correct for absorption by considering the probability
distribution for the column density conditioned on the hardness ratio is
presented. The binned luminosity function and its evolution is determined with
a variant of the Page-Carrera method, improved to include corrections for
absorption and to account for the full probability distribution of photometric
redshifts. Parametric models, namely a double power-law with LADE or LDDE
evolution, are explored using Bayesian inference. We introduce the
Watanabe-Akaike information criterion (WAIC) to compare the models and estimate
their predictive power. Our data are best described by the LADE model, as
hinted by the WAIC indicator. We also explore the 15-parameter extended LDDE
model recently proposed by Ueda et al., and find that this extension is not
supported by our data. The strength of our method is that it provides:
un-absorbed non-parametric estimates; credible intervals for luminosity
function parameters; model choice according to which one has more predictive
power for future data.Comment: In press on A&A. The revised version corrects typos and the LF
normalisations in tables 1,2,5 and figs.9-12, which were on an incorrect
scale. Online material available at
http://www.astro.lu.se/~piero/xlf/xlf-paper-tables2.tgz . The software is
available on the author's website
http://www.astro.lu.se/~piero/LFTools/index.html and on github:
https://github.com/piero-ranalli/LFTool
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