A simulation and control framework for AGV based transport systems
DATE:
2022-04
UNIVERSAL IDENTIFIER: http://hdl.handle.net/11093/3097
EDITED VERSION: https://doi.org/10.1016/j.simpat.2021.102430
UNESCO SUBJECT: 3307.99 Otras
DOCUMENT TYPE: article
ABSTRACT
This paper presents a flexible framework to simulate transport systems based on automated guided vehicles (AGVs). The framework used to perform the simulation also serves to implement the different policies and algorithms in the global control system. For all mobile platforms, regardless of their application, there is great interest in having the model in a simulation environment. However, transport systems tend to be complex, with many vehicles needing to execute many tasks at the same time. Furthermore, when analyzing the global control system, there is no need for a detailed simulation of each AGV. That is why most researchers do not use modular control frameworks, such as the robotic operating system (ROS), to simulate the global system. Instead, they use specific simulation tools that require the definition of the simulated scheduling, routing and allocation policies in specific languages or models. As an alternative, our approach extends the global control framework by replacing the on-board control modules and devices by an event simulator that models the AGV behavior statistically. With this approach, the control policies and methods are only implemented once; they are used and tested in simulation and later in the final system. Also, tasks are easily model and verified using a Petri Net-based model. This model is directly implemented in the executive module that coordinates all the other modules in the framework. This simulation framework has been used during the implementation of several projects which included an autonomous logistics system for hospitals, a warehouse internal transport system using autonomous forklifts, and a factory logistics transport system using tugger trains. Examples of how the simulation can help in the design of some parameters such as fleet size and scheduling policies are also included in the paper.