Modeling and Simulation of a Multi Robot System Architecture

• URL: http://arxiv.org/abs/2411.02468v1
• Date: Mon, 04 Nov 2024 14:00:43 GMT
• Title: Modeling and Simulation of a Multi Robot System Architecture
• Authors: Ahmed R. Sadik, Christian Goerick, Manuel Muehlig,
• Abstract summary: A Multi Robot System (MRS) is the infrastructure of an intelligent cyberphysical system, where the robots understand the need of the human. This paper introduces a general purpose MRS case study, where the humans initiate requests that are achieved by the available robots. Modeling an MRS is a crucial aspect of designing the proper system architecture, because this model can be used to simulate and measure the performance of the proposed architecture.
• Score: 0.3686808512438362
• License:
• Abstract: A Multi Robot System (MRS) is the infrastructure of an intelligent cyberphysical system, where the robots understand the need of the human, and hence cooperate together to fulfill this need. Modeling an MRS is a crucial aspect of designing the proper system architecture, because this model can be used to simulate and measure the performance of the proposed architecture. However, an MRS solution architecture modeling is a very difficult problem, as it contains many dependent behaviors that dynamically change due to the current status of the overall system. In this paper, we introduce a general purpose MRS case study, where the humans initiate requests that are achieved by the available robots. These requests require different plans that use the current capabilities of the available robots. After proposing an architecture that defines the solution components, three steps are followed. First is modeling these components via Business Process Model and Notation (BPMN) language. BPMN provides a graphical notation to precisely represent the behaviors of every component, which is an essential need to model the solution. Second is to simulate these components behaviors and interaction in form of software agents. Java Agent DEvelopment (JADE) middleware has been used to develop and simulate the proposed model. JADE is based on a reactive agent approach, therefore it can dynamically represent the interaction among the solution components. Finally is to analyze the performance of the solution by defining a number of quantitative measurements, which can be obtained while simulating the system model in JADE middleware, therefore the solution can be analyzed and compared to another architecture.

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