Publications
-
Double-Layer Soft Data Fusion for Indoor Robot WiFi-Visual Localization
This paper presents a novel WiFi-Visual data fusion method for indoor robot (TIAGO++) localization. Long-term follow-up experiments show that this method can use 10 WiFi samples and 4 low-resolution images ($58 times 58$ in pixels) to localize an indoor robot with an average error distance of about 1.32 meters 3 months (or 1.7 meters 7 […]
-
Building Fast Dynamic 3D Maps for Trajectory Planning of Autonomous Ground Vehicles Using Non-Repetitive Scanning LiDAR Sensor
Building fast and reliable maps of the environment is a fondamental task for autonomous navigation. However, this process offers several challenges such as accurate registration of 3D point clouds. Recently, non-repetitive scanning LiDAR sensors have emerged as a promising alternative for 3D data acquisition, leveraging some of these challenges. In this paper, we present a […]
-
A resource-constrained optimization model for parallel machine scheduling with constraint programming
This study investigates an NP-hard parallel machine scheduling problem, a critical challenge in manufacturing, healthcare, and logistics industries where efficient resource allocation is essential. The issue involves scheduling operations where each task requires an additional resource, with multiple resource types available, each limited to a single copy. The objective is to minimize the makespan, which […]
-
Chemical servoing with hexapod robot for gas source localization and YOLO‑based visual defect detection
Robotic systems have the ability to perform industrial inspection tasks through the integration of visual and chemical servoing functions. A commonly used system is the image-based servoing system. This study presents an innovative approach that merges chemical servoing with visual defect detection in industrial settings using a hexapod robot. The main goal is to develop […]
-
Etude de cas : L’optimisation d’une unité industrielle d’osmose inverse (OI) via l’intégration d’un jumeau numérique (JN) et de la réalité augmentée (RA).
L’osmose inverse (OI) est un procédé essentiel pour la production d’eau ultrapure dans divers secteurs industriels, mais son optimisation se heurte à des défis significatifs : complexité des paramètres physico-chimiques, maintenance prédictive des membranes, exigences de traçabilité et risques d’erreurs humaines [1-5]. L’émergence des technologies de l’Industrie 4.0, notamment le jumeau numérique (JN) [6, 8] […]
-
Role tension and perceived leadership influence on middle managers’ transformational leadership
Objectives & Literature Middle managers in the nuclear sector, as in other organizations, are key players in implementing policies and strategy. They are frequently exposed to paradoxical leadership styles and demands (Berti et Simpson, 2021). It gives rise to role tensions (i.e., role conflict, organizational cynicism, or cognitive dissonance) for middle managers (Razouk et Quéméner, […]
-
Intégration d’un jumeau numérique et définition collaborative de ses usages dans le cadre d’une pédagogie active
En appui sur le projet JENII, cette contribution se propose de documenter un cas d’usage lié à l’intégration du Jumeau Numérique d’un atelier de production industrielle à un bloc d’enseignement déjà établi depuis plusieurs années en classe préparatoire de formation d’ingénieur. L’étude de la logique de conception et des différents rôles remplis par les acteurs […]
-
Advanced Multi-Model Prediction of Aircraft Engine Remaining Useful Life with Random Sampling-Based Class Balancing and Voting-Based Features Selection
In Industry 4.0, predictive maintenance for critical systems like aircraft engines relies on accurate Remaining Useful Life (RUL) estimation to prevent unexpected failures and optimize maintenance schedules. However, existing models face several limitations that hinder their effectiveness in real-world applications. Common challenges include data imbalance, which can lead to biased predictions; suboptimal feature selection, which […]
-
A deep reinforcement learning-based multi-agent framework for dynamic optimization of qos in iot services
To address key challenges in IoT systems, including efficient resource allocation, adaptive service composition, and Quality of Service (QoS) under dynamic conditions, we develop a framework called DRL-MAS integrating multi-agent systems (MAS) and deep reinforcement learning (DRL). DRL-MAS leverages MAS’s decentralized decision-making capabilities and DRL’s adaptive learning strengths to ensure scalability, energy efficiency, and responsiveness […]
-
The Augmented Perception: an emerging approach toward resilient manufacturing systems involving robotic agents and digital twin.
This paper addresses the resilience of Industry 5.0 Manufacturing Systems (MS) with mobile robotic agents, focusing on robustness (handling disruptions while maintaining production) and flexibility (adapting to reconfigurations). We propose Augmented Perception (AP), a Digital Twin-based approach that enhances robot perception by integrating virtual elements in the map of the robot. Three use cases, in […]
-
Is fiscal countercyclicality growth enhancing? Evidence from developing countries over the period 1990–2019
The objective of this paper is to analyze the time-varying effect of improving fiscal countercyclicality on growth for a sample of 35 developing countries over the period 1990–2019. By estimating a time-varying coefficient for fiscal countercyclicality, incorporated as a variable in a panel model, we first examine how the public debt ratio and electoral motivations […]
-
Plastic optical fiber sensors for mooring lines monitoring in floating wind turbines: A reliability study of OTDR measurement
This study investigates the use of POF (Plastic Optical Fibers) for mooring lines monitoring in floating wind turbines. Focusing on their mechanical adaptability and optical performance in marine environments. Optical attenuation measurement are employed to determine integrity of POFs under mechanical stresses such as tension and torsion, as well as during prolonged water immersion at […]