Road detection and vehicles tracking by vision for ACC

This article deals with a process designed first to extract the lane of vehicle by on-board monocular vision. This detection process is based upon a recursive updating of a statistical model of the lane obtained by a training phase. Once the lane has been located, a reconstruction algorithm computes the vehicle location on its lane and the 3D shape of the road. Thereafter, we are focus at the detection, location and tracking of front vehicles equipped with specific visual markers in order to achieve an accurate determination of the location and speed of these vehicles. Merging these various informations allows to point out the most dangerous obstacle. Each of these three processes is detailed significant examples are provide.Cet article présente, dans un premier temps, un procédé permettant de détecter la voie de circulation d'un véhicule par vision monoculaire embarquée. Ce processus de détection est basé sur une mise à jour récursive d'un modèle statistique de la voie obtenu par une phase d'apprentissage. Après avoir localisé la voie, un algorithme de reconstruction détermine la position du véhicule dans sa voie de circulation et le profil 3D de la route. Par la suite, nous nous intéressons à la détection, la localisation et surtout le suivi des véhicules situés à l'avant et équipés de marques visuelles afin de déterminer avec précision la position et la vitesse relative de ces véhicules. La combinaison de ces différentes informations permet de déterminer le véhicule le plus dangereux. La description détaillée de chacune des étapes de notre algorithme est suivie d'exemples significatifs

Alcohol exposure during late gestation: Multiple developmental outcomes in sheep

Alcohol consumption during pregnancy remains common in many countries. Exposure to even low amounts of alcohol (i.e. ethanol) in pregnancy can lead to the heterogeneous fetal alcohol spectrum disorders (FASD), while heavy alcohol consumption can result in the fetal alcohol syndrome (FAS). FAS is characterized by cerebral dysfunction, growth restriction and craniofacial malformations. However, the effects of lower doses of alcohol during pregnancy, such as those that lead to FASD, are less well understood. In this article, we discuss the findings of recent studies performed in our laboratories on the effects of fetal alcohol exposure using sheep, in which we investigated the effects of late gestational alcohol exposure on the developing brain, arteries, kidneys, heart and lungs. Our studies indicate that alcohol exposure in late gestation can (1) affect cerebral white matter development and increase the risk of hemorrhage in the fetal brain, (2) cause left ventricular hypertrophy with evidence of altered cardiomyocyte maturation, (3) lead to a decrease in nephron number in the kidney, (4) cause altered arterial wall stiffness and endothelial and smooth muscle function and (5) result in altered surfactant protein mRNA expression, surfactant phospholipid composition and pro-inflammatory cytokine mRNA expression in the lung. These findings suggest that fetal alcohol exposure in late gestation can affect multiple organs, potentially increasing the risk of disease and organ dysfunction in later life

Commande de véhicule utilisant la reconnaissance d'indices image

Since several years, researchers attempt to design algorithms able to control a vehicle by using computer vision. Several approaches are now available but more often the vehicle control is achieved in separate way from the perception task. Indeed the vehicle state is combined with perception parameters to feed the regulation task. This paper presents the reliability of an original approach which combines perception and control task. The system we have designed is able to recognize roadsides from images cues in different situations (highway, road, etc), and to compute the vehicle wheel angle and several location parameters too. In particular, we present the need for achieving a training stage (given either by a control law or by a experimented human driver) to provide a good control law. The algorithm behavior is then presented in simulated and real situations as well in order to prove the reliability of the approach on an agricultural vehicle.Depuis plusieurs années, les chercheurs essayent de concevoir des algorithmes capables de commander un véhicule en employant la vision par ordinateur. Plusieurs approches sont maintenant disponibles mais le plus souvent, la commande du véhicule est réalisée en dehors de la tâche de perception. En effet l'état du vehicule est associé avec des paramètres de perception pour alimenter la tâche de régulation. Cet article présente la robustesse d'une approche originale qui combine la tâche de perception et la tâche de commande. Le système que nous avons conçu peut reconnaître les bords de la route à partir d'indices d'images en différentes situations (autoroute, route, etc..), et calculer l'angle des roues du véhicule ainsi que plusieurs paramètres de localisation. En particulier, nous présentons le besoin de la réalisation d'une étape d'apprentissage (réalisée par une loi de commande ou par un conducteur humain expérimenté) pour permettre une bonne loi de commande. Le comportement de l'algorithme est présenté dans des situations simulées et réelles sur un véhicule agricole

Cooperative localization based on range-only measurements from robots and infrastructure

International audienc

Near infrared reflectance spectroscopy to predict energy value of compound feeds for swine and ruminants

International audienc

Ruminal dry matter and nitrogen degradation in relation to condensed tannin and protein molecular structures in sainfoin (Onobrychis viciifolia) and lucerne (Medicago sativa).

Sainfoin is a temperate legume that contains condensed tannins (CT), i.e. polyphenols that are able to bind proteins and thus reduce protein degradation in the rumen. A reduction in protein degradation in the rumen can lead to a subsequent increase in amino acid flow to the small intestine. The effects of CT in the rumen and the intestine differ according to the amount and structure of CT and the nature of the protein molecular structure. The objective of the present study was to investigate the degradability in the rumen of three CT-containing sainfoin varieties and CT-free lucerne in relation to CT content and structure (mean degree of polymerization, proportion of prodelphinidins and cis-flavanol units) and protein structure (amide I and II bands, ratio of amide I-to-amide II, α-helix, β-sheet, ratio of α-helix-to-β-sheet). Protein molecular structures were identified using Fourier transform/infrared-attenuated total reflectance (FT/IR-ATR) spectroscopy. The in situ degradability of three sainfoin varieties (Ambra, Esparcette and Villahoz) was studied in 2008, during the first growth cycle at two harvest dates (P1 and P2, i.e. 5 May and 2 June, respectively) and at one date (P3) during the second growth cycle (2 June) and these were compared with a tannin-free legume, lucerne (Aubigny). Loss of dry matter (DMDeg) and nitrogen (NDeg) in polyester bags suspended in the rumen was measured using rumen-fistulated cows. The NDeg of lucerne compared with sainfoin was 0·80 v. 0·77 at P1, 0·78 v. 0·65 at P2 and 0·79 v. 0·70 at P3, respectively. NDeg was related to the rapidly disappearing fraction (‘a’) fraction (r=0·76), the rate of degradation (‘c’) (r=0·92), to the content (r=−0·81) and structure of CT. However, the relationship between NDeg and the slowly disappearing fraction (‘b’) was weak. There was a significant effect of date and species×date, for NDeg and ‘a’ fraction. The secondary protein structure varied with harvest date (species×date) and was correlated with the fraction ‘b’. Both tannin and protein structures influenced the NDeg degradation. CT content and structure were correlated to the ‘a’ fraction and to the ‘c’. Features of the protein molecular secondary structure were correlated to the ‘b’ fraction

Une démarche intégrée pour prévoir la valeur des aliments pour les ruminants : PrévAlim pour INRAtion

National audienceThis paper presents the bases of an integrated tool developed to estimate the feed value of forages and concentrates from their laboratory analysis. The computer program PrevAlim, available with the new version of INRAtion software, calculates the nutritive value of feed (feed unit UF and protein value PDI) and the fill unit (UE) of forages from the measurement of some characteristics of each feed. To calculate the nutritive value, a sequential approach is used, based on estimates of organic matter digestibility (dMO) and rumen degradability of feed protein (DT). UF and PDI values are then calculated using stepwise equations of the INRA (1988) systems. Estimates of the dMO are preferentially achieved from the enzymatic degradability method using pepsin-cellulase (dCs or dCo), or determined using the chemical composition of feed or the age of the plant. Estimates of the DT and the PDI values of concentrate feeds are achieved from the enzymatic degradability method using a protease (DE1). Fill values of forages are calculated from the estimates of their voluntary intakes based on their chemical composition or dMO. Equations for different types of forages are calculated from the INRA (1988) feed tables. PrevAlim integrates, co-ordinates and updates different tools already available (prediction of nutritive value) and a new one that estimates fill values of forages. The computer program ensures that the calculated values (UF, PDI and UE) are coherent with themselves and with the feed tables. The hierarchical approach we used allows 1- to estimate feed value even in case of some missing information 2- to choose the most relevant estimates in case of redundant information.Cet article présente les principes retenus pour élaborer le module de prévision de la valeur d’un aliment à partir des résultats de son analyse. Le module PrévAlim, proposé avec la nouvelle version d’INRAtion, permet de calculer à la fois la valeur nutritive (UF, PDI) et pour les fourrages la valeur d’encombrement (UE) à partir de la nature de l’aliment et de la mesure de certaines de ces caractéristiques. Pour la valeur nutritive, une démarche séquentielle a été adoptée, centrée sur l’estimation de la dMO et de la dégradabilité de l’azote (DT) ; le calcul des valeurs UF et PDI utilise ensuite la séquence des équations des systèmes INRA 1988. L’estimation de la dMO se fait soit préférentiellement à partir de la méthode de digestibilité enzymatique pepsine-cellulase (dCs ou dCo), soit à partir de la composition chimique ou de l’âge de la plante. L’estimation de la DT et de la valeur PDI des concentrés est basée sur la méthode enzymatique avec une protéase (DE1). La valeur d’encombrement des fourrages est calculée à partir de l’ingestibilité estimée directement à partir de la composition chimique ou de la dMO ; les équations par grandes classes d’aliments ont été déterminées sur la base des Tables INRA 1988. Ce module rassemble, coordonne et met à jour des outils déjà disponibles (Tables de prévision de 1981 et équations publiées depuis) et des outils créés spécialement (estimation des UE). Les valeurs calculées (UF, PDI et UE) sont cohérentes entre elles ainsi qu’avec celles des Tables. L’approche hiérarchisée adoptée permet de calculer les valeurs même avec des informations manquantes et de retenir la méthode d’évaluation la plus pertinente en cas d’informations redondantes