Publications
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Multi-Agent Cooperative Camera-Based Semantic Grid Generation
The idea of cooperative perception for navigation assistance was introduced about a decade ago with the aim to increase safety on dangerous areas like intersections. In this context, roadside infrastructure appeared very recently to provide a new point of view of the scene. In this paper, we propose to combine the Vehicle-To-Vehicle (V2V) and Vehicle-To-Infrastructure […]
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A Hybrid Binary Grey Wolf Optimiser for WSN Deployment in Indoor Environments Based on BIM database
Wireless Sensor Networks (WSNs) represent a key component in smart building systems. An efficient WSN deployment involves selecting the most appropriate positions within the building to place sensors in order to maximize coverage and minimize the deployment cost. This paper proposes a novel approach called the Hybrid Binary GreyWolf Optimiser (HBGWO) to automate the WSN […]
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DATA-DRIVEN PREDICTIVE ANALYSIS FOR CUTTING MACHINE FAILURES: A TECHNICAL REPORT ON RELIABILITY OPTIMIZATION
The prevention of recurring failures in modern manufacturing systems is of paramount importance for minimizing costs and downtime. Despite the potential for real-time data analysis using sensors offered by Industry 4.0 technologies, their widespread adoption, particularly among smaller manufacturing systems, remains a challenge. In response, this paper introduces an alternative approach to predictive maintenance planning, […]
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Introducing the 3MT_French dataset to investigate the timing of public speaking judgements
In most public speaking datasets, judgements are given after watching the entire performance, or on thin slices randomly selected from the presentations, without focusing on the temporal location of these slices. This does not allow to investigate how people’s judgements develop over time during presentations. This contrasts with primacy and recency theories, which suggest that […]
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Aging properties of a vegetable-based polyurethane foam under high relative humidity and different temperatures
The objective of this study is to assess, characterize, and forecast the aging effects on the mechanical properties of a vegetable-based polyurethane foam (PUF) derived from castor oil under elevated relative humidity conditions and at two distinct load orientations (aligned with the expansion direction and perpendicular to it). Ten specimens were subjected to temperatures of […]
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Exploiting Machine Learning Techniques to Predict the Stainless Steel Density Produced by Selective Laser Melting Additive Manufacturing
Porosity is one of the inherent defects that results from the Selective Laser Melting (SLM) additive manufacturing technique. The porosity related to fusion-solidification kinetics, results most often from non-optimally or poorly controlled manufacturing parameters. The density, a porosity indicator, affects the mechanical properties of the manufactured material (fatigue strength, cracks, deformations, etc.). Stainless steels are […]
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Application de systèmes multi-agents pour l’optimisation de la chaîne logistique industrielle
Dans le contexte dynamique des chaînes logistiques industrielles, l’optimisation des ressources est cruciale pour répondre aux exigences de plus en plus complexes du marché. La nécessité d’une gestion intégrée des ressources, englobant tant les machines de production que les moyens de transport, a émergé comme un impératif pour améliorer l’efficacité opérationnelle et maintenir la compétitivité. […]
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Integrating Human-Centricity, Sustainability, and Resilience in Digital Twin Models for Industry 5.0: A Multi-Objective Optimization Approach
This paper presents the InduDesc framework, an innovative digital twin model within the CupCarbon software, designed for the advanced needs of Industry 5.0. It integrates human-centred ergonomics, sustainability and resilience into the Flexible Job Shop Scheduling Problem (FJSP), traditionally an NP-hard challenge. By minimising operating times and balancing machine utilisation with ergonomic and sustainability considerations, […]
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Choix de fournisseurs sous une demande dynamique et des délais de livraison stochastiques
Ce travail traite du choix optimal des fournisseurs dans un contexte de demande dynamique et de délais de livraison stochastiques. L’étude propose plusieurs modèles linéaires stochastiques pour optimiser la répartition des commandes entre différents fournisseurs, en tenant compte des coûts d’achat, des pénalités de retard et des coûts de stockage. L’objectif est de minimiser le […]
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A polynomial algorithm for periodic scheduling
We are interested in problems related to periodic scheduling, driven by applications using networks in which terminals send identical flows periodically. The management of such flows must not only minimize latency, but also jitter, and we have shown that classical methods of sizing networks by statistical multiplexing are not suitable for this situation.
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Energy-efficient flexible flow shop scheduling with renewable energy sources and energy storage systems
In France, the industrial sector is responsible for 18% of the total energy consumption in 2023, nevertheless, only 7% of it comes from renewable energy sources [1]. With the increasing concern over climate change and global warming, industries have started to integrate programs based on demand-side management which includes energy efficiency and demand response to […]
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Improving Semantic Mapping with Prior Object Dimensions Extracted from 3D Models
Semantic mapping is a critical challenge that must be addressed to ensure the safe navigation of mobile robots. Equipping robots with semantic information enhances their interactions with humans, as well as their navigation and task planning capabilities. Semantic maps go beyond occupancy information, providing supplementary details about mapped elements that empower robots to gain a […]
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