Temporal Correlations and Persistence in the Kinetic Ising Model: the Role of Temperature

We study the statistical properties of the sum $S_t=\int_{0}^{t}dt' \sigma_{t'}$, that is the difference of time spent positive or negative by the spin $\sigma_{t}$, located at a given site of a $D$-dimensional Ising model evolving under Glauber dynamics from a random initial configuration. We investigate the distribution of $S_{t}$ and the first-passage statistics (persistence) of this quantity. We discuss successively the three regimes of high temperature ($T>T_{c}$), criticality ($T=T_c$), and low temperature ($T<T_{c}$). We discuss in particular the question of the temperature dependence of the persistence exponent $\theta$, as well as that of the spectrum of exponents $\theta(x)$, in the low temperature phase. The probability that the temporal mean $S_t/t$ was always larger than the equilibrium magnetization is found to decay as $t^{-\theta-\frac12}$. This yields a numerical determination of the persistence exponent $\theta$ in the whole low temperature phase, in two dimensions, and above the roughening transition, in the low-temperature phase of the three-dimensional Ising model.Comment: 21 pages, 11 PostScript figures included (1 color figure

Conception d'un système de localisation de source sonore large bande par formation de voie pour des applications robotiques

Le travail présenté dans cet article a été mené dans le cadre d'un projet visant au développement d'un capteur auditif pour la localisation de locuteur en robotique mobile. La méthode de localisation proposée s'appuie sur une formation de voie large bande déterminée par résolution d'un problème d'optimisation convexe. Une description précise de la procédure d'optimisation et de la chaîne d'acquisition utilisée sur la plateforme expérimentale est donnée de façon à faire le lien entre la théorie et son implémentation pratique. Des résultats de simulation ainsi que des comparaisons avec les techniques classiques de formation de voie sont également fournis

Otvoreno rješenje za estimaciju položaja humanoidnog robota integracijom senzora i proširenim Kalmanovim filtrom

In this paper an Extended Kalman Filter (EKF) is used in order to estimate the real state of a humanoid robot (HRP-2 robot in our case study) using the combination of the information coming from the encoders (kinematics) and from the Inertial Measurement Unit (IMU). The integration of the kinematic information into the Kalman filtering process allows a good estimation of the attitude and reduces the complexity of the problem to the use of simple kinematic transformations, even considering the existence of accelerations and mechanical flexibilities in the robot. The EKF estimator presented here is an open solution directly applicable to any humanoid robot, which is the main contribution of our approach. Experimental results are given showing the good performance of the method.U ovome članku koristi se prošireni Kalmanov filtar (EKF) za estimaciju stanja humanoidnog robota (HRP-2 robot) kombiniranjem informacija iz enkodera (kinematika) i inercijalne mjerne jedinice (IMU). Integracijom kinematičkih informacija u proces Kalmanovog filtra ostvaruje se dobra estimacija položaja i smanjenje složenosti problema jednostavnim kinematičkim transformacijama, čak i u slučaju postojanja akceleracija te mehaničkih savijanja robota. EKF predstavljen u ovome članku otvoreno je rješenje primjenjivo na bilo kojem humanoidnom robotu, što je i glavni doprinos predloženog pristupa. Ekperimentalni rezultati pokazuju dobro ponašanje predložene metode

Modélisation et commande d'un dirigeable pour le vol autonome

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Référentiels pour l'intégration multisensorielle et sensorimotrice (une approche neuro-robotique)

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Contribution à la synthèse de commandes référencées vision 2D multi-critères

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Path-Following with a Bounded-Curvature Vehicle: a Hybrid Control Approach

In this paper, we consider the problem of stabilizing the kinematic model of a car to a path in the plane under rather general conditions. The path is subject to very mild restrictions, while the car model, although rather simplified, contains the most relevant limitations inherent in wheeled robots kinematics. Namely, the car can only move forward, its steering radius is lower bounded and a limited sensory information only provides a partial knowledge of some state parameters. In particular, we consider the case that the current distance and the heading angle error with respect to the closest point on the reference path can be measured but only the sign of the path curvature is detected. These constraints are such to make classical control techniques inefficient. As the feedback information is both continuous and discrete, the hybrid systems formalism turns out to be well appropriate to model the problem. The proposed approach is based on optimal control techniques successfully applied in a previous work for following rectilinear path. We propose here an extension to the tracking of more general paths with moderate curvature. The stability of the closed-loop system is proved by means of the hybrid system formalism and hybrid formal verification techniques. Finally, the practicality of the proposed approach, in spite of non--idealities in real-world applications, is discussed by reporting experimental results

Génération de mouvements corps-complet sous contraintes pour des systèmes dynamiques anthropomorphes

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Optimal feedback control for line tracking with a bounded--curvature vehicle

The problem of driving a vehicle along a given path is considered. The vehicle is supposed to move forward only, with a given velocity profile, and to have a bounded turning radius. Such a model, also known as 'Dubins' vehicle', is relevant to the kinematics of road vehicles as well as aircraft cruising at constant altitude, or sea vessels. We consider the optimal control problem consisting of minimizing the length travelled by the vehicle starting from a generic configuration to connect to a specified route. A feedback law is proposed, such that straight routes can be approached optimally, while the system is asymptotically stabilized. Experimental results are reported showing real-time feasibility of the proposed approach