54,770 research outputs found
Nonlinear Constraint Network Optimization for Efficient Map Learning
No full textLearning models of the environment is one of the fundamental tasks of mobile robots since maps are needed for a wide range of robotic applications, such as navigation and transportation tasks, service robotic applications, and several others. In the past, numerous efficient approaches to map learning have been proposed. Most of them, however, assume that the robot lives on a plane. In this paper, we present a highly efficient maximum-likelihood approach that is able to solve 3-D and 2-D problems. Our approach addresses the so-called graph-based formulation of simultaneous localization and mapping (SLAM) and can be seen as an extension of Olson's algorithm toward non-flat environments. It applies a novel parameterization of the nodes of the graph that significantly improves the performance of the algorithm and can cope with arbitrary network topologies. The latter allows us to bound the complexity of the algorithm to the size of the mapped area and not to the length of the trajectory. Furthermore, our approach is able to appropriately distribute the roll, pitch, and yaw error over a sequence of poses in 3-D mapping problems. We implemented our technique and compared it with multiple other graph-based SLAM solutions. As we demonstrate in simulated and real-world experiments, our method converges faster than the other approaches and yields accurate maps of the environment
On Actively Closing Loops in Grid-based FastSLAM
No full textAcquiring models of the environment belongs to the fundamental tasks of mobile robots. In the past, several researchers have focused on the problem of simultaneous localization and mapping (SLAM). Classical SLAM approaches are passive in the sense that they only process the perceived sensor data and do not influence the motion of the mobile robot. In this paper, we present a novel integrated approach that combines autonomous exploration with simultaneous localization and mapping. Our method uses a grid-based version of the FastSLAM algorithm and considers at each point in time actions to actively close loops during exploration. By re-entering already visited areas, the robot reduces its localization error and in this way learns more accurate maps. Experimenta
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Letter from C. D. Dawson, Tusayan Copper Mining and Smelting, to Carl Hayden
No full textLetter from C. D. Dawson to Carl Hayden urging him to consider the rights of miners and farmers when drawing up the boundaries for the proposed park
Measurement of the D+/- production asymmetry in 7 TeV pp collisions
No full textThe asymmetry in the production cross-section \sigma of D+/- mesons, A_P = (\sigma(D+) - \sigma(D-))/(\sigma(D+) + \sigma(D-)), is measured in bins of pseudorapidity \eta and transverse momentum p_T within the acceptance of the LHCb detector. The result is obtained with a sample of D+ -> K_S pi+ decays corresponding to an integrated luminosity of 1.0 fb^-1, collected in pp collisions at a centre of mass energy of 7 TeV at the Large Hadron Collider. When integrated over the kinematic range 2.0 K_S pi+ decay is negligible. No significant dependence on \eta or p_T is observed
D* (D)over-bar* molecule interpretation of Z(c)(4025)
No full textWe have used QCD sum rules to study the newly observed charged state Z(c)(4025) as a hidden-charm D*(D) over bar* molecular state with the quantum numbers I-G(J(P)) =1(+)(1(+)). Using a D*(D) over bar* molecular interpolating current, we have calculated the two-point correlation function and the spectral density up to dimension eight at leading order in alpha(s). The extracted mass is m(X) = (4.04 +/- 0.24) GeV. This result is compatible with the observed mass of Z(c)(4025) within the errors, which implies a possible molecule interpretation of this new resonance. We also predict the mass of the corresponding hidden-bottom B*(B) over bar* molecular state: m(Zb) = (9.98 +/- 0.21) GeV.Physics, Particles & FieldsSCI(E)[email protected]; [email protected]; [email protected]; [email protected]
Prompt charm production in pp collisions at √<span style="text-decoration:overline">s</span>=7 TeV
No full textCharm production at the LHC in pp collisions at s√=7 TeV is studied with the LHCb detector. The decays D0→K−π+, D+→K−π+π+, D⁎+→D0(K−π+)π+, D+s→ϕ(K−K+)π+, Λ+c→pK−π+, and their charge conjugates are analysed in a data set corresponding to an integrated luminosity of 15 nb−1. Differential cross-sections dσ/dpT are measured for prompt production of the five charmed hadron species in bins of transverse momentum and rapidity in the region 0<pT<8 GeV/c and 2.0<y<4.5. Theoretical predictions are compared to the measured differential cross-sections. The integrated cross-sections of the charm hadrons are computed in the above pT-y range, and their ratios are reported. A combination of the five integrated cross-section measurements gives
σ(cc¯)pT<8 GeV/c,2.0<y<4.5=1419±12(stat)±116(syst)±65(frag) μb,
where the uncertainties are statistical, systematic, and due to the fragmentation functions
Online constraint network optimization for efficient maximum likelihood map learning
No full textIn this paper, we address the problem of incrementally optimizing constraint networks for maximum likelihood map learning. Our approach allows a robot to efficiently compute configurations of the network with small errors while the robot moves through the environment. We apply a variant of stochastic gradient descent and use a tree-based parameterization of the nodes in the network. By integrating adaptive learning rates in the parameterization of the network, our algorithm can use previously computed solutions to determine the result of the next optimization run. Additionally, our approach updates only the parts of the network which are affected by the newly incorporated measurements and starts the optimization approach only if the new data reveals inconsistencies with the network constructed so far. These improvements yield an efficient solution for this class of online optimization problems. Our approach has been implemented and tested on simulated and on real data. We present comparisons to recently proposed online and offline methods that address the problem of optimizing constraint network. Experiments illustrate that our approach converges faster to a network configuration with small errors than the previous approaches. ©2008 IEEE
Z(c)(3900) as a (D)over-barD* molecule from the pole counting rule
No full textA comprehensive study on the nature of the Zc(3900) resonant structure is carried out in this work. By constructing the pertinent effective Lagrangians and considering the important final-state-interaction effects, we first give a unified description to all the relevant experimental data available, including the J/psi pi and pi invariant mass distributions from the e(+)e(-) -> J/psi pi process, the h(c)pi distribution from e(+)e(-) -> h(c)pi pi, and also the D (D) over bar* spectrum in the e(+)e(-) -> D (D) over bar*pi process. After fitting the unknown parameters to the previous data, we search the pole in the complex energy plane and find only one pole in the nearby energy region in different Riemann sheets. Therefore, we conclude that Z(c)(3900) is of D (D) over bar* molecular nature, according to the pole counting rule method [Nucl. Phys. A543, 632 (1992); Phys. Rev. D 35, 1633 (1987)]. We emphasize that the conclusion based upon the pole counting method is not trivial, since both the D (D) over bar* contact interactions and the explicit Z(c) exchanges are introduced in our analyses andNational Nature Science Foundations of China (NSFC) [10925522, 11021092, 11575052, 11105038]; Natural Science Foundation of Hebei Province [A2015205205]; inoGerman Collaborative Research Center "Symmetries and the Emergence of Structure in QCD" [CRC 110]; DFG; NSFCSCI(E)ARTICLE119
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