HAL : Dernières publications

• [hal-00782079] Utilisation de polynômes de Tchebychev pour l'identification de modèles à temps continu de robots

  Dans cet article, une présentation des propriétés des polynômes de Tchebychev et une formulation dérivée utilisant ces polynômes sont effectuées. La méthode d'identification présentée consiste à appliquer une transformation linéaire sur le système d'équations qui régit le processus. Pour cela, l'opérateur mathématique utilisé s'appuie sur une décomposition du signal dans une base formée de polynômes orthogonaux. Nous montrons que cette projection se comporte comme un filtre passe-bande, de telle sorte qu'une seule opération est nécessaire pour le pré-traitement des données avant le processus d'identification, à savoir choisir la dimension de la base des polynômes Tchebychev. Une identification expérimentale en boucle fermée d'un robot à 2 axes avec cette méthode est effectuée dans une dernière partie. Les résultats obtenus sont comparés et analysés avec d'autres techniques utilisées en robotique.

• [hal-01467446] A revised Durbin-Wu-Hausman test for industrial robot identification

  This paper addresses the topic of robot identification. The usual identification method makes use of the inverse dynamic model (IDM) and the least squares (LS) technique while robot is tracking exciting tra- jectories. Assuming an appropriate bandpass filtering, good results can be obtained. However, the users are in doubt whether the columns of the observation matrix (the regressors) are uncorrelated (exo- genous) or correlated (endogenous) with the error terms. The exogeneity condition is rarely verified in a formal way whereas it is a fundamental condition to obtain unbiased LS estimates. In Econometrics, the Durbin-Wu-Hausman test (DWH-test) is a formal statistic for investigating whether the regressors are exogenous or endogenous. However, the DWH-test cannot be straightforwardly used for robot identifi- cation because it is assumed that the set of instruments is valid. In this paper, a Revised DWH-test suitable for robot identification is proposed. The revised DWH-test validates/invalidates the instruments chosen by the user and validates the exogeneity assumption through the calculation of the QR factor- ization of the augmented observation matrix combined with a F-test if required. The experimental results obtained with a 6 degrees-of-freedom (DOF) industrial robot validate the proposed statistic.

• [hal-01061255] Comparison between the CLOE Method and the DIDIM Method for Robots Identification

  This brief deals with the identification of industrial robots. The usual identification method is based on the use of the inverse dynamic identification model and the least-squares technique. Another approach is the direct and inverse dynamic identification models (DIDIM) method, which is a closed-loop output error (CLOE) method minimizing the quadratic error between the actual and simulated joint torques. In this brief, the DIDIM method is compared with the usual CLOE method, which minimizes the quadratic error between the actual and simulated joint positions. The comparison is carried out on six degrees of freedom industrial robot. The experimental results show that the DIDIM method needs three iterations to identify 60 parameters while the usual CLOE method needs 20 iterations.

• [hal-00954732] An instrumental variable approach for rigid industrial robots identification

  This paper deals with the important topic of rigid industrial robots identification. The usual identification method is based on the use of the inverse dynamic model and the least-squares technique. In order to obtain good results, a well-tuned derivative bandpass filtering of joint positions is needed to calculate the joint velocities and accelerations. However, we can doubt whether the bandpass filter is well-tuned or not. Another approach is the instrumental variable (IV) method which is robust to data filtering and which is statistically optimal. In this paper, an IV approach relevant for identification of rigid industrial robots is introduced. The set of instruments is the inverse dynamic model built from simulated data which are calculated from the simulation of the direct dynamic model. The simulation assumes the same reference trajectories and the same control structure for both the actual and the simulated robot and is based on the previous IV estimates. Furthermore, to obtain a rapid convergence, the gains of the simulated controller are updated according to IV estimates. Thus, the proposed approach validates the inverse and direct dynamic models simultaneously and is not sensitive to initial conditions. The experimental results obtained with a 2 degrees of freedom (DOF) planar prototype and with a 6 DOF industrial robot show the effectiveness of our approach: it is possible to identify 60 parameters in 3 iterations and in 11 s.

• [hal-00941612] Generic instrumental variable approach for industrial robot identification

  This paper deals with the important topic of industrial robot identification. The usual identification method is based on the inverse dynamic identification model and the least squares technique. This method has been successfully applied on several industrial robots. Good results can be obtained, provided a well tuned derivative band-pass filtering of joint positions is used to calculate the joint velocities and accelerations. However, one cannot be sure whether or not the band-pass filtering is well tuned. An alternative is the instrumental variable (IV) method, which is robust to data filtering and is statistically optimal. In this paper, a generic IV approach suitable for robot identification is proposed. The instrument set is the inverse dynamic model built from simulated data calculated from simulation of the direct dynamic model. The simulation is based on previous estimates and assumes the same reference trajectories and the same control structure for both actual and simulated robots. Finally, gains of the simulated controller are updated according to IV estimates to obtain a valid instrument set at each step of the algorithm. The proposed approach validates the inverse and direct dynamic models simultaneously, is not sensitive to initial conditions, and converges rapidly. Experimental results obtained on a six-degrees-of-freedom industrial robot show the effectiveness of this approach: 60 dynamic parameters are identified in three itérations.

• [hal-00850643] A New Closed-Loop Output Error Method for Parameter Identification of Robot Dynamics

  Offline robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sampled while the robot is tracking reference trajectories that excite the system dynamics. This allows using linear least-squares techniques to estimate the parameters. The efficiency of this method has been proved through the experimental identification of many prototypes and industrial robots. However, this method requires the joint force/torque and position measurements and the estimate of the joint velocity and acceleration, through the bandpass filtering of the joint position at high sampling rates. The proposed new method called DIDIM requires only the joint force/torque measurement, which avoids the calculation of the velocity and acceleration by bandpass filtering of the measured position. It is a closed-loop output error method where the usual joint position output is replaced by the joint force/torque. It is based on a closed-loop simulation of the robot using the direct dynamic model, the same structure of the control law, and the same reference trajectory for both the actual and the simulated robot. The optimal parameters minimize the 2-norm of the error between the actual force/torque and the simulated force/torque. This is a nonlinear least-squares problem which is dramatically simplified using the inverse dynamic model to obtain an analytical expression of the simulated force/torque, linear in the parameters. A validation experiment on a two degree-of-freedom direct drive rigid robot shows that the new method is efficient.

• [hal-00851507] Identification of Physical Parameters and Instrumental Variables Validation With Two-Stage Least Squares Estimator

  This paper addresses physical parameters identification of mathematical models that are linear in relation to these physical parameters. We can obtain good results with the least squares technique, provided that a well-tuned data filtering is used, and by using instrumental variable (IV) methods, which deal with the problem of noisy observation matrix. However, IV theory is based on instruments validity. In econometrics, statistical tests evaluating instruments quality have been developed. They make use of the two-stage least squares estimator and the concentration parameter introduced by Basmann. In this paper we show how to extend econometric theory to control engineering. An algorithm evaluating instruments quality is presented and experimentally validated on a two-degrees-of-freedom SCARA robot.

• [hal-00638013] New results on the relation between tyre-road longitudinal stiffness and maximum available grip for motor car

  Tyre-road estimation methods have been the objective of many research programmes throughout the world. Most of these methods aim at estimating the friction components such as tyre longitudinal slip rate κ and friction coefficient μ in the contact patch area. In order to estimate the maximum available friction coefficient μmax , these methods generally use a probabilistic relationship between the grip obtained for low tyre excitations (such as constant speed driving) and the grip obtained for high tyre excitations (such as emergency braking manoeuvre). Confirmation or invalidation of this relationship from experimental results is the purpose of this paper. Experiments have been carried out on a reference track including several test boards corresponding to a wide textural spectrum. The main advantage of these experiments lies in the use of a vehicle allowing us to accurately build point-by-point relationship between κ and μ. This relationship has been determined for different tyres and pavement textures. Finally, the curves obtained are analysed to check the validity of the relationship between the current friction coefficient used by the car during normal driving conditions and μmax.

• [hal-04030611] Enhancement of Vehicle Eco-Driving Applicability through Road Infrastructure Design and Exploitation

  Energy moderation of the road transportation sector is required to limit climate change and to preserve resources. This work is focused on the moderation of vehicle consumption by optimizing the speed policy along an itinerary while taking into account vehicle dynamics, driver visibility and the road's longitudinal profile. First, a criterion is proposed in order to detect speed policies that are impeding drivers' eco-driving ability. Then, an energy evaluation is carried out and an optimization is proposed. A numerical application is performed on a speed limiting point with 20 usage cases and 5 longitudinal slope values. In the hypothesis of a longitudinal slope of zero, energy savings of 27.7 liter per day could be realized by a speed sign displacement of only 153.6 m. Potential energy savings can increase to up to 308.4 L per day for a −4% slope case, or up to 70.5 L per day for an ordinary −2% slope, with a sign displacement of only 391.5 m. This results in a total of 771,975 L of fuel savings over a 30 year infrastructure life cycle period. Therefore a methodology has been developed to help road managers optimize their speed policies with the aim of moderating vehicle consumption.

• [hal-02868022] Vehicle energy savings by optimizing road speed-sectioning

  In a context of decreasing resources and of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. This work aims to demonstrate that road energy demand and associated pollutant emissions can be reduced by working out minor optimization of road infrastructure itself. For this to happen, a simple eco-driving potential criterion is built upon infrastructure parameters such as slopes and sight distances. This criterion aims to detect Misplaced Speed-sectioning Positions (MSP) with regard to the Starting Point of Deceleration (SPD); with speed-sectioning being the succession of speed changes along a given route. An enhanced energy waste formulation is then developed to quantify the vehicles energy waste due to misplaced road-signs. Thirdly, a traffic simulation constitutes a framework for energy evaluation; considering a full flow of vehicles, based on real traffic data, and by modeling several driver behaviors. Simulation results show that a significant fuel reduction of up to 5.5% can be achieved locally, simply by moving a road sign, for rural areas and without degrading road safety.

• [hal-03196270] Generating a two-layered synthetic population for French municipalities: Results and evaluation of four synthetic reconstruction methods

  This article describes the generation of a detailed two-layered synthetic population of households and individuals for French municipalities. Using French census data, four synthetic reconstruction methods associated with two probabilistic integerization methods are applied. The paper offers an in-depth description of each method through a common framework. A comparison of these methods is then carried out on the basis of various criteria. Results show that the tested algorithms produce realistic synthetic populations with the most efficient synthetic reconstruction methods assessed being the Hierarchical Iterative Proportional Fitting and the relative entropy minimization algorithms. Combined with the Truncation Replication Sampling allocation method for performing integerization, these algorithms generate household-level and individual-level data whose values lie closest to those of the actual population.

• [hal-03500363] Multi-scale spatial analysis of household car ownership using distance-based Moran's eigenvector maps: Case study in Loire-Atlantique (France)

  Analyzing spatial structures of transportation data at various scales can be of prime interest to transportation planning and governance. In recent years, multi-scale spatial analysis methods have been developed and used in fields like ecology and geography, but only a few studies have applied these methods to transportation data. However, such methods can provide an efficient exploratory tool for: identifying those scales at which transportation data vary spatially; modeling the spatial structures at each scale; and determining the processes at work that explain these spatial structures. This paper describes and demonstrates how a multi-scale spatial analysis method, namely distance-based Moran's eigenvector maps (dbMEM), can be applied to study the spatial layout of car ownership. For this analysis, we rely on aggregated census data for small statistical areas within France's Loire-Atlantique administrative region. At first, 176 spatial vectors representing spatial patterns with a positive autocorrelation are constructed. Among the 176 vectors, only 23 significant ones are retained after performing a regression with car ownership as the dependent variable. Next, we divide these spatial vectors into three sub-models representing three spatial scales: broad scale, medium scale, and fine scale. Lastly, we identify a set of sociodemographic factors capable of explaining the spatial variation at each scale, i.e.: the broad-scale variation is mainly explained by population density, couples with children and income variables; the medium scale by couples with children, share of individuals in the 25-54 year age range and income; and the fine scale by couples with children and income variables.

• [hal-03081480] Comparing Methods for Generating a Two-Layered Synthetic Population

  Synthetic population is used in many transport models ranging from trip-based, hybrid trip, tour-based, and activity-based models. As mobility decisions depend on both individuals' characteristics and family situation, generating a two-layered population that takes into account not only the individual level but also household level is essential. In the literature, three main categories of methods for two-layered population generation have been proposed. These categories are synthetic reconstruction (SR), combinatorial optimization (CO), and statistical learning (SL). SR and CO methods produce synthetic populations by means of replicating individuals, whereas SL methods generate a population following a joint probability estimation. However, selecting a generation process is not straightforward as it depends on input data and synthetic population characteristics. To the best of our knowledge, no clear methodology for selecting between these methods exists. The main objectives of this paper are to provide (1) a detailed description of the available methods, (2) a comparison between these methods, and (3) a decision-making procedure for selecting between these methods. The description and comparison of the methods relies on different criteria: marginals availability, sample size, number of potential attributes that can be handled, population size to generate, possibility of zero-cell problem, and so forth. The advantages and shortcomings of each method are illustrated, and method performance is assessed. The decision-making procedure is carried out through the proposal of a decision tree. Researchers and practitioners have now access to a comprehensive and unified framework to select the appropriate method depending on available data and features of their modeling purposes.

• [hal-02482046] Analyse de trajectoires fluviales à partir de données SIA pour la conception d’une passerelle

  La Métropole Rouen Normandie souhaitait concevoir une nouvelle passerelle nécessitant des appuis provisoires en Seine. Aussi a-t-elle sollicité l’Ifsttar pour conduire une étude statistique des données de trajectoires, afin de définir les fuseaux de mobilité des navires en fonction notamment de leur vitesse et de leur gabarit, deux facteurs susceptibles d’avoir un impact sur la manoeuvrabilité des navires. Le traitement des données au format SIA a nécessité de recourir à des outils dédiés aux gros fichiers de données. Puis un modèle de régression linéaire a été retenu pour l’analyse des trajectoires rectilignes hors manoeuvres d’accostage. La détermination d’intervalles de prédiction a permis de délimiter les zones de navigation, et donc de mettre en évidence les surfaces du fleuve aptes à accueillir les appuis provisoires.

• [hal-01578913] Towards eco-aware timetabling: evolutionary approach and cascading initialisation strategy for the bi-objective optimisation of train running times

  In railway planning, the timetabling step needs, as input, the train running times, which are calculated from a train dynamic model. Usually, this model determines the most energy-efficient train trajectory for a predefined time. However, this time may not correspond to the timetable-makers' needs. They should have the choice among a set of solutions, more or less energy-consuming. This study proposes a method capable of producing a set of alternative running times with the associated mechanical energy required. To this end, the authors' contribution is to set up an efficient evolutionary multi-objective algorithm builds a set of well-spread and diversified solutions which approximate a Pareto front. The solutions are all compromises between running time and energy-consumption, the two minimisation objectives concurrently optimised. Given that an evolutionary algorithm is strongly dependent on the initialisation phase, the efficiency of the algorithm is improved through a specific and original mechanism connecting multiple initialisations in cascade in order to accelerate the convergence towards the best solutions. A set of results obtained on randomly-generated instances is analysed and discussed.

• [hal-03081371] Slope Optimization (or "Sloop"): Customized Optimization for Road Longitudinal Profile Eco-Design

  Current transportation systems contributed to one quarter to the Greenhouse Gases (GhG) emissions and the mobility demand increases continuously. The transportation infrastructure design has to be optimized to mitigate these emissions. The methodology ?Sloop? (acronym for Slope Optimization) has recently been set up to optimize the longitudinal road profile with respect to a Global Warming Potential (GWP) criterion calculated for both the construction and operational phases while incorporating accurate vehicle models. This paper proposes a customized optimization strategy that significantly improves the Sloop methodology. From an initial longitudinal profile generated by road designers, our algorithm identifies the optimized profile in terms of GWP. This optimization step is complex due to the large number of degrees of freedom, along with various constraints to obtaining a feasible solution and the computational cost of the operational phase assessment. The most stringent constraint entails connecting the profile with the existing road (i.e., a constraint on the final profile altitude). We have developed a specific algorithm based on the Sequential Quadratic Programming (SQP) method; this algorithm takes into account the quasi-quadratic nature of the constraint on the final altitude. In a real case study, our algorithm outputs a profile whose GWP assessment saves 4% compared to the GWP assessment of the initial profile. The benefit of our specific protocol for treating the final altitude constraint is demonstrated in this example. By means of this new efficient and open-box algorithm, profile evolution at each iteration is analyzed to determine the most sensitive degrees of freedom, and the sensitivity of the optimization with respect to the main construction parameters and traffic assumptions are conducted. The results are consistent and stable.

• [hal-01835743] Eco-design model of a railway: A method for comparing the energy consumption of two project variants

  In accordance with the environmental concerns that national policies still address throughout the world, railways have been extensively studied to provide quantified indicators for assessing construction/operations practices. It is essential to take energy consumption, into account since energy can be measured worldwide, in addition to constituting a global environmental load that is time-limited as regards resource availability and known as a discriminating criterion in comparing transport infrastructure. This article introduces an innovative, generic and systemic method dedicated to determining the energy consumption of a railway line during the pre-project phase by taking into account the complete life cycle of the rail infrastructure, including construction, maintenance and operations. The method developed (called PEAM ) focuses on assessing project variants during the design stage and therefore integrates both the geometric longitudinal constraints of the line and the thicknesses/volumes over the entire itinerary as design parameters for input into the various construction scenarios. PEAM combines methodologies stemming from life cycle assessment with a consumption model derived from physical modeling. The models associated with this method are then applied to study the energy consumption of a new high-speed line located in France that also has major implications for the European connections currently under investigation as well. Two project variants are compared in terms of total energy for a 50-year service life and a given characteristic rail traffic, including passenger and freight flows. Results obtained reveal a 30% difference between the two variants, which prior to applying PEAM were considered to be relatively similar.

• [hal-02005356] Longitudinal profile optimization for roads within an eco-design framework

  This paper proposes a methodology to optimize the longitudinal profile of roads according to either an energy consumption or Global Warming Potential (GWP) criterion calculated for both construction and operation phases. For the construction phase assessment, this methodology is based on a earthworks model that computes the geometric differences between the natural terrain and the longitudinal road profile and moreover uses environmental data validated with real experiments. The operation phase is assessed by simulating traffic over a ten-years period. Traffic simulations are based on vehicle dynamic models, also validated with real experiments. The optimization problem is set up in a finite dimensional optimization. A case study illustrates this methodology. By taking into account actual traffic measurements, the optimized profile decreases by 6% the total primary energy consumption and by 8% the GWP.

• [hal-01670595] Évaluation de l’adhérence de pneumatiques sur pistes comme un paramètre de la sécurité des métros automatiques

  Les métros automatiques, sans conducteurs, sont en déploiement important depuis des décennies et offrent de hauts niveaux de service et de sécurité. S’affranchir du facteur humain peut en effet augmenter ces niveaux en exploitation courante mais des protocoles robustes de commande sont alors requis pour pallier l’absence des qualités humaines d’anticipation et d’adaptation en situations exceptionnelles. De tels protocoles, dits d’anti‐collision, sont généralement basés sur une performance minimale de freinage garantie associée à un découpage de l’infrastructure en cantons, fixes ou mobiles, assurant qu’il ne puisse y avoir simultanément plus d’un véhicule sur le même canton. En particulier, un système de métro automatique sur pneu est présenté dans cet article. Des résultats d’essais de freinage de rames montrent l’efficacité de traitements visant à améliorer l’adhérence pneumatique/piste de roulement. L’entretien des pistes pour maintenir un bon niveau de freinage est discuté pour les techniques courantes de striage et de grenaillage des pistes. Enfin, une méthodologie pour permettre le suivi des pistes en temps et en espace est proposée. Elle inclut la sélection et l’emploi de matériels d’évaluation de l’adhérence issus du domaine routier.

• [hal-00960333] Application of viability theory for road vehicle active safety during cornering manoeuvres

  Viability theory proposes geometric metaphors in addition to classical ordinary differential equation analysis. In this paper, advantages of applying viability theory to road safety domain are presented. The exact issue is to determine if, from an initial state of a vehicle/road/driver system, a soft controls strategy is compatible with a safe driving sequence. The case of a car negotiating a curve is considered. The application of the viability theory to this issue offers the advantage to avoid classical full computing of the system. Instead of that, it consists on verifying that the states and the controls belong to a subset called the viability kernel. The construction and the use of the viability kernel for a vehicle system dynamic is proposed by using support vector machines algorithm. Then, the applicability of this theory is demonstrated through experimental tests. This innovative application of the viability theory to vehicle dynamics with road safety concerns could benefit to robust embedded warning systems.