A New Dataset of People Flow in an Industrial Site with UWB and Motion Capture Systems

Mickael Delamare (1) , Fabrice Duval (2) , Rémi Boutteau (3, 4)

1 IRSEEM - Institut de Recherche en Systèmes Electroniques Embarqués
2 LINEACT - Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires
3 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
4 STI - LITIS - Equipe Systèmes de Transport Intelligent

Flexible manufacturing systems (FMS) are used to ensure the production of several products using the same set of production tools. Transportation tasks using robots are introduced in order to increase the routing flexibility of the FMS. Several researchers are interested in the optimization of the production planning but few of them considered the transportation planning. On another hand, each optimization algorithm needs an adapted control architecture to be executed. In this paper, we propose the use of a hybrid architecture control to implement the bi-objective optimization algorithm based on Multi-Objective Genetic Algorithm (MOGA). Results showing the efficiency of the proposed approach are presented.

Keywords: Task Assignment Optimization Auction Robots Transportation tasks; Task Assignment; Optimization; Auction; Robots; Transportation tasks

Domains: Computer Science [cs]

Mickael Delamare, Fabrice Duval, Rémi Boutteau. A New Dataset of People Flow in an Industrial Site with UWB and Motion Capture Systems. Sensors, 2020, 20 (16), pp.4511. ⟨10.3390/s20164511⟩. ⟨hal-02937349⟩