Deep Semantic Classification for 3D LiDAR Data

Robots are expected to operate autonomously in dynamic environments. Understanding the underlying dynamic characteristics of objects is a key enabler for achieving this goal. In this paper, we propose a method for pointwise semantic classification of 3D LiDAR data into three classes: non-movable, movable and dynamic. We concentrate on understanding these specific semantics because they characterize important information required for an autonomous system. Non-movable points in the scene belong to unchanging segments of the environment, whereas the remaining classes corresponds to the changing parts of the scene. The difference between the movable and dynamic class is their motion state. The dynamic points can be perceived as moving, whereas movable objects can move, but are perceived as static. To learn the distinction between movable and non-movable points in the environment, we introduce an approach based on deep neural network and for detecting the dynamic points, we estimate pointwise motion. We propose a Bayes filter framework for combining the learned semantic cues with the motion cues to infer the required semantic classification. In extensive experiments, we compare our approach with other methods on a standard benchmark dataset and report competitive results in comparison to the existing state-of-the-art. Furthermore, we show an improvement in the classification of points by combining the semantic cues retrieved from the neural network with the motion cues.Comment: 8 pages to be published in IROS 201

Arrow's theorem for weak orders

We characterize binary decision rules which are independent and strongly paretian,or independent and almost strongly paretian when the individual preferences and the collective preference are weak orders.Binary decision rule, lexicographic dictatorship

Dependence of the electronic structure of self-assembled InGaAs/GaAs quantum dots on height and composition

While electronic and spectroscopic properties of self-assembled In_{1-x}Ga_{x}As/GaAs dots depend on their shape, height and alloy compositions, these characteristics are often not known accurately from experiment. This creates a difficulty in comparing measured electronic and spectroscopic properties with calculated ones. Since simplified theoretical models (effective mass, k.p, parabolic models) do not fully convey the effects of shape, size and composition on the electronic and spectroscopic properties, we offer to bridge the gap by providing accurately calculated results as a function of the dot height and composition. Prominent results are the following. (i) Regardless of height and composition, the electron levels form shells of nearly degenerate states. In contrast, the hole levels form shells only in flat dots and near the highest hole level (HOMO). (ii) In alloy dots, the electrons' ``s-p'' splitting depends weakly on height, while the ``p-p'' splitting depends non-monotonically. In non-alloyed InAs/GaAs dots, both these splittings depend weakly on height. For holes in alloy dots, the ``s-p'' splitting decreases with increasing height, whereas the ``p-p'' splitting remains nearly unchaged. Shallow, non-alloyed dots have a ``s-p'' splitting of nearly the same magnitude, whereas the ``p-p'' splitting is larger. (iii) As height increases, the ``s'' and ``p'' character of the wavefunction of the HOMO becomes mixed, and so does the heavy- and light-hole character. (iv) In alloy dots, low-lying hole states are localized inside the dot. Remarkably, in non-alloyed InAs/GaAs dots these states become localized at the interface as height increases. This localization is driven by the biaxial strain present in the nanostructure.Comment: 14 pages, 12 figure

Quantum Monte Carlo study of dilute neutron matter at finite temperatures

We report results of fully non-perturbative, Path Integral Monte Carlo (PIMC) calculations for dilute neutron matter. The neutron-neutron interaction in the s channel is parameterized by the scattering length and the effective range. We calculate the energy and the chemical potential as a function of temperature at the density \dens=0.003\fm^{-3}. The critical temperature \Tc for the superfluid-normal phase transition is estimated from the finite size scaling of the condensate fraction. At low temperatures we extract the spectral weight function $A(p,\omega)$ from the imaginary time propagator using the methods of maximum entropy and singular value decomposition. We determine the quasiparticle spectrum, which can be accurately parameterized by three parameters: an effective mass $m^*$, a mean-field potential $U$, and a gap $\Delta$. Large value of \Delta/\Tc indicates that the system is not a BCS-type superfluid at low temperatures.Comment: 4 pages, 3 figure

Statistical investigation and thermal properties for a 1-D impact system with dissipation

The behavior of the average velocity, its deviation and average squared velocity are characterized using three techniques for a 1-D dissipative impact system. The system -- a particle, or an ensemble of non interacting particles, moving in a constant gravitation field and colliding with a varying platform -- is described by a nonlinear mapping. The average squared velocity allows to describe the temperature for an ensemble of particles as a function of the parameters using: (i) straightforward numerical simulations; (ii) analytically from the dynamical equations; (iii) using the probability distribution function. Comparing analytical and numerical results for the three techniques, one can check the robustness of the developed formalism, where we are able to estimate numerical values for the statistical variables, without doing extensive numerical simulations. Also, extension to other dynamical systems is immediate, including time dependent billiards.Comment: To appear in Physics Letters A (2016

Dark-matter dynamical friction versus gravitational-wave emission in the evolution of compact-star binaries

The measured orbital period decay of compact-star binaries, with characteristic orbital periods $\sim 0.1$~days, is explained with very high precision by the gravitational wave (GW) emission of an inspiraling binary in vacuum. However, the binary gravitational binding energy is also affected by an usually neglected phenomenon, namely the dark matter dynamical friction (DMDF) produced by the interaction of the binary components with their respective DM gravitational wakes. The entity of this effect depends on the orbital period and on the local value of the DM density, hence on the position of the binary in the Galaxy. We evaluate the DMDF produced by three different DM profiles: the Navarro-Frenk-White (NFW), the non-singular-isothermal-sphere (NSIS) and the Ruffini-Arg\"uelles-Rueda (RAR) profile based on self-gravitating keV fermions. We first show that indeed, due to their Galactic position, the GW emission dominates over the DMDF in the NS-NS, NS-WD and WD-WD binaries for which measurements of the orbital decay exist. Then, we evaluate the conditions under which the effect of DMDF on the binary evolution becomes comparable to, or overcomes, the one of the GW emission. We find that, for instance for $1.3$--$0.2$ $M_\odot$ NS-WD, $1.3$--$1.3$~$M_\odot$ NS-NS, and $0.25$--$0.50$~$M_\odot$ WD-WD, located at 0.1~kpc, this occurs at orbital periods around 20--30 days in a NFW profile while, in a RAR profile, it occurs at about 100 days. For closer distances to the Galactic center, the DMDF effect increases and the above critical orbital periods become interestingly shorter. Finally, we also analyze the system parameters for which DMDF leads to an orbital widening instead of orbital decay. All the above imply that a direct/indirect observational verification of this effect in compact-star binaries might put strong constraints on the nature of DM and its Galactic distribution.Comment: 15 pages, 12 figures, 2 tables, accepted for publication in Phys. Rev. D, 201