- RIUMA Principal
- Listar por autor
Listar por autor "Adeogun, Ramoni"
Mostrando ítems 1-2 de 2
-
Distributed deep reinforcement learning resource allocation scheme for industry 4.0 Device-To-Device scenarios
Burgueño Romero, Jesús; Adeogun, Ramoni; Liborius Bruun, Rasmus; Morejón García, C. Santiago; De la Bandera Cascales, Isabel; Barco-Moreno, Raquel[et al.] (2021)This paper proposes a distributed deep reinforcement learning (DRL) methodology for autonomous mobile robots (AMRs) to manage radio resources in an indoor factory with no network infrastructure. Hence, deep neural networks ... -
Proactive dual connectivity for automated guided vehicles in outdoor industrial environment
Mendoza, Jessica; Kovács, István Z.; López, Melisa; Sørensen, Troels B.; Adeogun, Ramoni; De la Bandera Cascales, Isabel; Barco-Moreno, Raquel[et al.] (IEEE, 2022)5G communication systems are one of the major enabling technologies to meet the needs of Industry 4.0. This paper focuses on the use case of automated guided vehicles (AGVs) in an outdoor industrial scenario. To meet the ...