Comparison of Two Objects Classification Techniques using Hidden Markov Models and Convolutional Neural Networks

This paper presents a comparison between discrete Hidden Markov Models and Convolutional Neural Networks for the image classification task. By fragmenting an image into sections, it is feasible to obtain vectors that represent visual features locally, but if a spatial sequence is established in a fixed way, it is possible to represent an image as a sequence of vectors. Using clustering techniques, we obtain an alphabet from said vectors and then symbol sequences are constructed to obtain a statistical model that represents a class of images. Hidden Markov Models, combined with quantization methods, can treat noise and distortions in observations for computer vision problems such as the classification of images with lighting and perspective changes. We have tested architectures based on three, six and nine hidden states favoring the detection speed and low memory usage. Also, two types of ensemble models were tested. We evaluated the precision of the proposed methods using a public domain data set, obtaining competitive results with respect to fine-tuned Convolutional Neural Networks, but using significantly less computing resources. This is of interest in the development of mobile robots with computers with limited battery life, but requiring the ability to detect and add new objects to their classification systems

A SLAM system based on Hidden Markov Models

Methods of simultaneous localization and mapping (SLAM) are a solution for the navigation problem of service robots. We present a graph SLAM system based on Hidden Markov Models (HMM) where the sensor readings are represented with different symbols using a number of clustering techniques; then, the symbols are fused as a single prediction, to improve the accuracy rate, using a Dual HMM. Our system’s versatility allows to work with different types of sensors or fusion of sensors, and to implement, either active or passive, graph SLAM. A graph-SLAM approach proposed by the International’s Karto Robotics in Cartographer, the nodes represent the pose of the robot and the edges the constraints between them. Nodes are usually defined according to contiguous nodes except when loop closures are detected where constraints for non-contiguous nodes are introduced, which corrects the whole graph. Detecting loop closure is not trivial; in the ROS implementation, scan matching is performed by Sparse Pose Adjustment (SPA). Cartographer uses an occupancy map in order to estimate the position where the map representation is done via Gmapping. The Toyota HSR (Human Support Robot) robot was used to generate the data set in both real and simulated competition environments. In our SLAM representation, we have wheel odometry estimate according to initial position of the robot, a Hokuyo 2D Lidar scan for observations, and a signal control and a world representation is estimated. We tested our system in the kidnapped robot problem by training a representation, improving it online, and, finally, solving the SLAM problem

Teleoperated Service Robot with an Immersive Mixed Reality Interface

Teleoperated service robots can perform more complex and precise tasks as they combine robot skills and human expertise. Communication between the operator and the robot is essential for remote operation and strongly affects system efficiency. Immersive interfaces are being used to enhance teleoperation experience. However, latency or time delay can impair the performance of the robot operation. Since remote visualization involves transmitting a large amount of video data, the challenge is to decrease communication instability. Then, an efficient teleoperation system must have a suitable operation interface capable of visualizing the remote environment, controlling the robot, and having a fast response time. This work presents the development of a service robot teleoperation system with an immersive mixed reality operation interface where the operator can visualize the real remote environment or a virtual 3D environment representing it. The virtual environment aims to reduce the latency on communication by reducing the amount of information sent over the network and improve user experience. The robot can perform navigation and simple tasks autonomously or change to the teleoperated mode for more complex tasks. The system was developed using ROS, UNITY 3D, and sockets to be exported with ease to different platforms. The experiments suggest that having an immersive operation interface provides improved usability for the operator. The latency appears to improve when using the virtual environment. The user experience seems to benefit from the use of mixed reality techniques; this may lead to the broader use of teleoperated service robot systems

Measurement of the p-pbar -> Wgamma + X cross section at sqrt(s) = 1.96 TeV and WWgamma anomalous coupling limits

The WWgamma triple gauge boson coupling parameters are studied using p-pbar -> l nu gamma + X (l = e,mu) events at sqrt(s) = 1.96 TeV. The data were collected with the DO detector from an integrated luminosity of 162 pb^{-1} delivered by the Fermilab Tevatron Collider. The cross section times branching fraction for p-pbar -> W(gamma) + X -> l nu gamma + X with E_T^{gamma} > 8 GeV and Delta R_{l gamma} > 0.7 is 14.8 +/- 1.6 (stat) +/- 1.0 (syst) +/- 1.0 (lum) pb. The one-dimensional 95% confidence level limits on anomalous couplings are -0.88 < Delta kappa_{gamma} < 0.96 and -0.20 < lambda_{gamma} < 0.20.Comment: Submitted to Phys. Rev. D Rapid Communication

Measurement of the ttbar Production Cross Section in ppbar Collisions at sqrt{s} = 1.96 TeV using Kinematic Characteristics of Lepton + Jets Events

We present a measurement of the top quark pair ttbar production cross section in ppbar collisions at a center-of-mass energy of 1.96 TeV using 230 pb**{-1} of data collected by the DO detector at the Fermilab Tevatron Collider. We select events with one charged lepton (electron or muon), large missing transverse energy, and at least four jets, and extract the ttbar content of the sample based on the kinematic characteristics of the events. For a top quark mass of 175 GeV, we measure sigma(ttbar) = 6.7 {+1.4-1.3} (stat) {+1.6- 1.1} (syst) +/-0.4 (lumi) pb, in good agreement with the standard model prediction.Comment: submitted to Phys.Rev.Let

Measurement of the B0_s semileptonic branching ratio to an orbitally excited D_s** state, Br(B0_s -> Ds1(2536) mu nu)

In a data sample of approximately 1.3 fb-1 collected with the D0 detector between 2002 and 2006, the orbitally excited charm state D_s1(2536) has been observed with a measured mass of 2535.7 +/- 0.6 (stat) +/- 0.5 (syst) MeV via the decay mode B0_s -> D_s1(2536) mu nu X. A first measurement is made of the branching ratio product Br(b(bar) -> D_s1(2536) mu nu X).Br(D_s1(2536)->D* K0_S). Assuming that D_s1(2536) production in semileptonic decay is entirely from B0_s, an extraction of the semileptonic branching ratio Br(B0_s -> D_s1(2536) mu nu X) is made.Comment: 7 pages, 2 figures, LaTeX, version with minor changes as accepted by Phys. Rev. Let

Search for R-parity violating supersymmetry via the LLE couplings lambda_{121}, lambda_{122} or lambda_{133} in ppbar collisions at sqrt(s)=1.96 TeV

A search for gaugino pair production with a trilepton signature in the framework of R-parity violating supersymmetry via the couplings lambda_121, lambda_122, or lambda_133 is presented. The data, corresponding to an integrated luminosity of L~360/pb, were collected from April 2002 to August 2004 with the D0 detector at the Fermilab Tevatron Collider, at a center-of-mass energy of sqrt(s)=1.96 TeV. This analysis considers final states with three charged leptons with the flavor combinations eel, mumul, and eetau (l=e or mu). No evidence for supersymmetry is found and limits at the 95% confidence level are set on the gaugino pair production cross section and lower bounds on the masses of the lightest neutralino and chargino are derived in two supersymmetric models.Comment: 9 pages, 4 figures (fig2 includes 3 subfigures

Measurement of the ttbar Production Cross Section in ppbar Collisions at sqrt(s)=1.96 TeV using Lepton + Jets Events with Lifetime b-tagging

We present a measurement of the top quark pair ($t\bar{t}$) production cross section ($\sigma_{t\bar{t}}$) in $p\bar{p}$ collisions at $\sqrt{s}=1.96$ TeV using 230 pb$^{-1}$ of data collected by the D0 experiment at the Fermilab Tevatron Collider. We select events with one charged lepton (electron or muon), missing transverse energy, and jets in the final state. We employ lifetime-based b-jet identification techniques to further enhance the $t\bar{t}$ purity of the selected sample. For a top quark mass of 175 GeV, we measure $\sigma_{t\bar{t}}=8.6^{+1.6}_{-1.5}(stat.+syst.)\pm 0.6(lumi.)$ pb, in agreement with the standard model expectation.Comment: 7 pages, 2 figures, 3 tables Submitted to Phys.Rev.Let

Simultaneous measurement of the ratio B(t->Wb)/B(t->Wq) and the top quark pair production cross section with the D0 detector at sqrt(s)=1.96 TeV

We present the first simultaneous measurement of the ratio of branching fractions, R=B(t->Wb)/B(t->Wq), with q being a d, s, or b quark, and the top quark pair production cross section sigma_ttbar in the lepton plus jets channel using 0.9 fb-1 of ppbar collision data at sqrt(s)=1.96 TeV collected with the D0 detector. We extract R and sigma_ttbar by analyzing samples of events with 0, 1 and >= 2 identified b jets. We measure R = 0.97 +0.09-0.08 (stat+syst) and sigma_ttbar = 8.18 +0.90-0.84 (stat+syst)} +/-0.50 (lumi) pb, in agreement with the standard model prediction.Comment: submitted to Phys.Rev.Letter