Publications
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Éléments d’état de l’art sur la cartographie sémantique et son applicabilité en environnement industriel
La sécurité dans la collaboration homme-robot est l’un des principaux défis de l’industrie 5.0. Les robots doivent à présent s’adapter à l’humain. Ils évaluent et améliorent le système de navigation sur la base de technologies de cartographie sémantique qui permet de conduire un raisonnement clair. Ces cartes permettent aux robots de comprendre l’environnement qui les […]
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Integration of Augmented, Virtual and Mixed Reality with Building Information Modeling: A Systematic Review
Thanks to the digital revolution, the construction industry has seen a recognizable evolution, where the world has been heading towards modern constructions based on the use of Building Information Modeling (BIM). This evolution was marked by the integration of this paradigm with immersive technologies like Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). […]
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Human-centred assembly and disassembly systems: a survey on technologies, ergonomic, productivity and optimisation
Despite the increasing use of automation in the current industry 4.0 context, manual assembly and disassembly tasks are still common and in some situations even unavoidable. The interaction between humans and other elements of the Assembly and Disassembly Systems (ADS) has been discussed in the scientific literature with the dual objective of optimising human well-being […]
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Simulation and Optimisation of a Failure-Prone Disassembly-Reconditioning-Assembly System
This paper deals with the simulation and optimisation of disassembly-reconditioningassembly system (DRAS) taken into account random machines failures and repairs. The proposed system is composed of one disassembly machine, two parallel structures, one assembly machine and stocks to store the used products, components and finished product. In this study a complete disassembly and assembly process […]
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Two-stage stochastic program for disassembly lot-sizing under random ordering lead time
This study addresses disassembly lot-sizing that determines the ordering and disassembly schedules of end-of-life (EOL) products and subassemblies to satisfy items demands. A stochastic version with uncertain ordering lead time (OLT) is considered for the first time. Here, OLT represents the time elapsed between placing an order and receiving it (only an EOL product can […]
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Sim-optimization hybrid approach for scheduling randomly deteriorating treatment tasks in horticulture
In this paper, we study the problem of scheduling robotized tasks in the context of Agriculture 4.0. The objective is to optimize the treatment tasks of plants against an evolving disease (mildew) within a greenhouse. The treatment is performed using a type-C ultraviolet radiation (UV-C) by a UV-Robot. We propose a semi-dynamic simulation-optimization approach based […]
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Modeling and simulation of human behavior impact on production throughput
The development of new technologies generates intelligent, complex, and collaborative production systems. Several research works want to improve the production performances while improving the comfort of the human operator. However, it is not obvious to define optimal strategies of operations planning and control that consider the unexpected and variable character of human operators. It is […]
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Community-based method for extracting backbones
Networks are an adequate representation for modeling and analyzing a great variety of complex systems. However, understanding networks with millions of nodes and billions of connections can be pretty challenging due to memory and time constraints. Therefore, selecting the relevant nodes and edges of these large-scale networks while preserving their core information is a major […]
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Improved Hourly Prediction of BIPV Photovoltaic Power Building Using Artificial Learning Machine: A Case Study
In the energy transition, controlling energy consumption is a challenge for everyone, especially for BIPV (Building Integrated Photovoltaics) buildings. Artificial Intelligence is an efficient tool to analyze fine prediction with a better accuracy. Intelligent sensors are implemented on the different equipments of a BIPV building to collect information and to take decision about the energy […]
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Accelerated Variant of Reinforcement Learning Algorithms for Light Control with Non-Stationary User Behaviour
In the context of smart building energy management, we address in this work the problem of controlling light so as to minimise energy usage of the building while maintaining the satisfaction of the user regarding comfort using a stateless Reinforcement Learning approach. We consider that the user can freely interact with the building and changes […]
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Stable keypoints selection for 2D LiDAR based place recognition with map data reduction
This paper presents a new feature based approach for place recognition using 2D LiDAR (Light Detection And Ranging) data. The main contribution lies in the mapping process. It includes a keypoint selection strategy to model places with persistent keypoints from concatenated LiDAR scans. Our objective is to achieve map data reduction while maintaining good place […]
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