Control of a Biped Robot by Total Rate of Angular Momentum Using the Task Function Approach

In this work we address the control problem of biped robots by using the task function approach. A problem arrives when one of the feet is in contact with the ground, which presents imperfections. There is then the possibility that the biped robot undergoes a fall. It is difficult to track any trajectory due to the presence of unevenness on the ground. What we propose is to use the task function approach combined with the application of the total rate of angular momentum to obtain a control law for the ankle. By this technique, the tracking becomes more smooth and the balance is assured. The control law proposed allows the upper part of the robot to be controlled independently since only the ankle actuators are concerned. We enounce the formal problem and present some simulations with real parameters of a 21 degrees of freedom biped robot

Status of maturation of critical technologies and systems design: Breeding blanket

The scope of the EUFOfusion Work Package Breeding Blanket is to develop a blanket concept for the EU DEMO reactor; this includes the blanket segments inside the Vacuum Vessel and the related Tritium Extraction/Removal Systems. In the Pre-Concept Design (PCD) Phase, two concepts have been selected as candidates; a solid and a liquid breeder blanket cooled with helium and water, respectively. The design of these two blanket systems has been adapted to the DEMO plant design developed in the PCD Phase and performances assessed. A large R&D programme has been implemented with the scope to evaluate different technologies for these blankets; including the development of breeders, tritium extraction and cooling technologies, and the manufacturing of the blanket system. A major milestone in the subsequent Concept Design Phase is the final selection of the blanket concept for DEMO

Legged Robots

International audienc

Measurement of substructure-dependent jet suppression in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

The ATLAS detector at the Large Hadron Collider has been used to measure jet substructure modification and suppression in Pb+Pb collisions at a nucleon–nucleon center-of-mass energy √sNN = 5.02 TeV in comparison with proton–proton (pp) collisions at √s = 5.02 TeV. The Pb+Pb data, collected in 2018, have an integrated luminosity of 1.72 nb−1, while the ppdata, collected in 2017, have an integrated luminosity of 260 pb−1. Jets used in this analysis are clustered using the anti-kt algorithm with a radius parameter R = 0.4. The jet constituents, defined by both tracking and calorimeter information, are used to determine the angular scale rg of the first hard splitting inside the jet by reclustering them using the Cambridge–Aachen algorithm and employing the soft-drop grooming technique. The nuclear modification factor, RAA, used to characterize jet suppression in Pb+Pb collisions, is presented differentially in rg, jet transverse momentum, and in intervals of collision centrality. The RAA value is observed to depend significantly on jet rg. Jets produced with the largest measured rg are found to be twice as suppressed as those with the smallest rg in central Pb+Pb collisions. The RAA values do not exhibit a strong variation with jet pT in any of the rg intervals. The rg and pT dependence of jet RAA is qualitatively consistent with a picture of jet quenching arising from coherence and provides the most direct evidence in support of this approach

Anomaly detection search for new resonances decaying into a Higgs boson and a generic new particle X in hadronic final states using Formula Presented pp collisions with the ATLAS detector

A search is presented for a heavy resonance Formula Presented decaying into a Standard Model Higgs boson Formula Presented and a new particle Formula Presented in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at Formula Presented collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of Formula Presented. The search targets the high Formula Presented-mass region, where the Formula Presented and Formula Presented have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted Formula Presented particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark Formula Presented decay into two quarks, covering topologies where the Formula Presented is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into Formula Presented, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section Formula Presented) for signals with Formula Presented between 1.5 and 6 TeV and Formula Presented between 65 and 3000 GeV. A search is presented for a heavy resonance Y decaying into a Standard Model Higgs boson H and a new particle X in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at √ s = 13     TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139     fb − 1 . The search targets the high Y -mass region, where the H and X have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted X particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark X decay into two quarks, covering topologies where the X is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into b ¯ b , and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section σ ( p p → Y → X H → q ¯ q b ¯ b ) for signals with m Y between 1.5 and 6 TeV and m X between 65 and 3000 GeV

Performance of the ATLAS forward proton Time-of-Flight detector in Run 2

We present performance studies of the Time-of-Flight (ToF) subdetector of the ATLAS Forward Proton (AFP) detector at the LHC. Efficiencies and resolutions are measured using high-statistics data samples collected at low and moderate pile-up in 2017, the first year when the detectors were installed on both sides of the interaction region. While low efficiencies are observed, of the order of a few percent, the resolutions of the two ToF detectors measured individually are 21 ps and 28 ps, yielding an expected resolution of the longitudinal position of the interaction, z vtx, in the central ATLAS detector of 5.3 ± 0.6 mm. This is in agreement with the observed width of the distribution of the difference between z vtx, measured independently by the central ATLAS tracker and by the ToF detector, of 6.0 ± 2.0 mm

Measurement of exclusive pion pair production in proton–proton collisions at √s=7 TeV with the ATLAS detector

The exclusive production of pion pairs in the process pp→ ppπ+π- has been measured at s=7TeV with the ATLAS detector at the LHC, using 80μb-1 of low-luminosity data. The pion pairs were detected in the ATLAS central detector while outgoing protons were measured in the forward ATLAS ALFA detector system. This represents the first use of proton tagging to measure an exclusive hadronic final state at the LHC. A cross-section measurement is performed in two kinematic regions defined by the proton momenta, the pion rapidities and transverse momenta, and the pion–pion invariant mass. Cross-section values of 4.8±1.0(stat)-0.2+0.3(syst)μb and 9±6(stat)-2+2(syst)μb are obtained in the two regions; they are compared with theoretical models and provide a demonstration of the feasibility of measurements of this type

Constraints on Higgs boson properties using WW∗(→ eνμν) jj production in 36.1fb-1 of √s=13 TeV pp collisions with the ATLAS detector

This article presents the results of two studies of Higgs boson properties using the WW∗(→ eνμν) jj final state, based on a dataset corresponding to 36.1 fb - 1 of s=13 TeV proton–proton collisions recorded by the ATLAS experiment at the Large Hadron Collider. The first study targets Higgs boson production via gluon–gluon fusion and constrains the CP properties of the effective Higgs–gluon interaction. Using angular distributions and the overall rate, a value of tan (α) = 0.0 ± 0.4 (stat.) ± 0.3 (syst.) is obtained for the tangent of the mixing angle for CP-even and CP-odd contributions. The second study exploits the vector-boson fusion production mechanism to probe the Higgs boson couplings to longitudinally and transversely polarised W and Z bosons in both the production and the decay of the Higgs boson; these couplings have not been directly constrained previously. The polarisation-dependent coupling-strength scale factors are defined as the ratios of the measured polarisation-dependent coupling strengths to those predicted by the Standard Model, and are determined using rate and kinematic information to be aL=0.91-0.18+0.10(stat.)-0.17+0.09(syst.) and aT= 1.2 ± 0.4 (stat.)-0.3+0.2(syst.). These coupling strengths are translated into pseudo-observables, resulting in κVV=0.91-0.18+0.10(stat.)-0.17+0.09(syst.) and ϵVV=0.13-0.20+0.28 (stat.)-0.10+0.08(syst.). All results are consistent with the Standard Model predictions