Synchronisation et calibrage entre un Lidar 3D et une centrale inertielle pour la localisation précise d'un véhicule autonome

International audienceLaser remote sensing (Lidar) is a technology increasingly used especially in the perception layers of autonomous vehicles. As the vehicle moves during measurement, Lidar data must be referenced in a fixed frame which is usually done thanks to an inertial measurement unit (IMU). However, these sensors are not designed to work together natively thus it is necessary to synchronize and calibrate them carefully. This article presents a method for characterizing timing offsets between a 3D Lidar and an inertial measurement unit. It also explains how to implement the usual methods for pose estimation between an IMU and a Lidar when using such sensors in real conditions.La télédétection par laser (Lidar) est une technologie de plus en plus utilisée en particulier dans les fonctions de perception et localisation nécessaires à la conduite autonome. L'acquisition des données Lidar doit être couplée à la mesure du mouvement du véhicule par une centrale inertielle. Ces capteurs n'étant pas conçus pour fonctionner ensemble nativement, il est nécessaire de maitriser leur synchronisation et leur calibrage géométrique. Cet article présente une méthode pour caractériser les décalages temporels entre un Lidar 3D et une centrale inertielle. Il explique aussi comment mettre en œuvre les méthodes de la littérature pour le calcul de la pose entre centrale inertielle et Lidar sur un véhicule utilisé en conditions réelles

Bypass and hyperbole in soil science:A perspective from the next generation of soil scientists

International audienceWe, the co‐authors of this letter, are an international group of soil scientists at early career stages, from PhD students to postdoctoral researchers, lecturers, and research fellows with permanent positions. Here, we present our collective musings on soil research challenges and opportunities and, in particular, the points raised by Philippe Baveye (Baveye, 2020a, 2020b) and Johan Bouma (Bouma, 2020) on bypass and hyperbole in soil science. Raising awareness about these issues is a first and necessary step. To this end, we would like to thank Philippe Baveye and Johan Bouma for initiating this debate.......

Replenishment planning for stochastic inventory systems with shortage cost

One of the most important policies adopted in inventory control is the (R,S) policy (also known as the "replenishment cycle" policy). Under the non-stationary demand assumption the (R,S) policy takes the form (R/sub n/,S/sub n/) where R/sub n/ denotes the length of the n/sup th/ replenishment cycle, and S/sub n/ the corresponding order-up-to-level. Such a policy provides an effective means of damping planning instability and coping with demand uncertainty. In this paper we develop a CP approach able to compute optimal (R/sub n/,S/sub n/) policy parameters under stochastic demand, ordering, holding and shortage costs. The convexity of the cost-function is exploited during the search to compute bounds. We use the optimal solutions to analyze the quality of the solutions provided by an approximate MIP approach that exploits a piecewise linear approximation for the cost function.Anglai

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

An anomaly detection approach to monitor the structure-based navigation in agricultural robotics

International audienc

A Vision-Based System for Robot Localization in Large Industrial Environments

International audienc

Synchronisation et calibrage entre un Lidar 3D et une centrale inertielle pour la localisation précise d'un véhicule autonome GEOLOCALISATION ET NAVIGATION Synchronisation et calibrage entre un Lidar 3D et une centrale inertielle pour la localisation precise d'un véhicule autonome Synchronization and calibration between a 3D Lidar and an inertial measurement unit for the accurate localization of an autonomous vehicle

Synchronisation et calibrage entre un Lidar 3D et une centrale inertielle pour la localisation précise d'un véhicule autonom

Synchronisation et calibrage entre un Lidar 3D et une centrale inertielle pour la localisation précise d'un véhicule autonome GEOLOCALISATION ET NAVIGATION Synchronisation et calibrage entre un Lidar 3D et une centrale inertielle pour la localisation precise d'un véhicule autonome Synchronization and calibration between a 3D Lidar and an inertial measurement unit for the accurate localization of an autonomous vehicle

Synchronisation et calibrage entre un Lidar 3D et une centrale inertielle pour la localisation précise d'un véhicule autonomeLa télédétection par laser (Lidar) est une technologie de plus en plus utilisée en particulier dans les fonctions de perception et localisation nécessaires à la conduite autonome. L'acquisition des données Lidar doit être couplée à la mesure du mouvement du véhicule par une centrale inertielle. Ces capteurs n'étant pas conçus pour fonctionner ensemble nativement, il est nécessaire de maitriser leur synchronisation et leur calibrage géométrique. Cet article présente une méthode pour caractériser les décalages temporels entre un Lidar 3D et une centrale inertielle. Il explique aussi comment mettre en oeuvre les méthodes de la littérature pour le calcul de la pose entre centrale inertielle et Lidar sur un véhicule utilisé en conditions réelles. Abstract: Laser remote sensing (Lidar) is a technology increasingly used especially in the perception layers of autonomous vehicles. As the vehicle moves during measurement, Lidar data must be referenced in a fixed frame which is usually done thanks to an inertial measurement unit (IMU). However, these sensors are not designed to work together natively thus it is necessary to synchronize and calibrate them carefully. This article presents a method for characterizing timing offsets between a 3D Lidar and an inertial measurement unit. It also explains how to implement the usual methods for pose estimation between an IMU and a Lidar when using such sensors in real conditions