Mechatronic modelling of industrial AGVs: a complex system architecture

Automatic guided vehicles (AGVs) are unmanned transport vehicles widely used in the industry to substitute manned industrial trucks and conveyors. They are now considered to play a key role in the development of the Industry 4.0 due to their temporal and spatial flexibility. However, in order to dea...

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Detalles Bibliográficos
Autores: Sierra-García, Jesús Enrique, Santos Peñas, Matilde
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/112249
Acceso en línea:https://hdl.handle.net/20.500.14352/112249
Access Level:acceso abierto
Palabra clave:Modelling
Automated guided vehicle (AGV)
Mechatronic
Física-Modelos matemáticos
3311.02 Ingeniería de Control
Descripción
Sumario:Automatic guided vehicles (AGVs) are unmanned transport vehicles widely used in the industry to substitute manned industrial trucks and conveyors. They are now considered to play a key role in the development of the Industry 4.0 due to their temporal and spatial flexibility. However, in order to deal with the AGV as a potential mobile robot with high capacities and certain level of intelligence, it is necessary to develop control-oriented models of these complex and nonlinear systems. In this paper, the modelling of this vehicle as a whole is addressed. It can be considered composed of several interrelated subsystems: control, safety, driving, guiding and localization, power storage, and charging systems. The kinematics equations of a tricycle vehicle are obtained, and a controller is proposed. An extended hybrid automata formalism is used to define the behaviour of the safety and the control systems, as well as their interaction. In addition, the electrical equivalent circuit of the batteries, charger, and the motors is studied. The architecture of the holistic model is presented. Simulation results of the AGV in a workspace scenario validate the model and prove the efficiency of this approach.