Model-Driven Simulation-Based Analysis for Multi-Robot Systems

J. Harbin, Simos Gerasimou, N. Matragkas, Athanasios Zolotas, R. Calinescu
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引用次数: 4

Abstract

Multi-robot systems are increasingly deployed to provide services and accomplish missions whose complexity or cost is too high for a single robot to achieve on its own. Although multi-robot systems offer increased reliability via redundancy and enable the execution of more challenging missions, engineering these systems is very complex. This complexity affects not only the architecture modelling of the robotic team but also the modelling and analysis of the collaborative intelligence enabling the team to complete its mission. Existing approaches for the development of multi-robot applications do not provide a systematic mechanism for capturing these aspects and assessing the robustness of multi-robot systems. We address this gap by introducing ATLAS, a novel model-driven approach supporting the systematic robustness analysis of multi-robot systems in sim-illation. The ATLAS domain-specific language enables modelling the architecture of the robotic team and its mission, and facilitates the specification of the team's intelligence. We evaluate ATLAS and demonstrate its effectiveness on two oceanic exploration missions performed by a team of unmanned underwater vehicles developed using the MOOS-IvP robotic simulator.
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基于模型驱动仿真的多机器人系统分析
多机器人系统越来越多地用于提供服务和完成复杂或成本太高的任务,单个机器人无法单独完成。尽管多机器人系统通过冗余提供了更高的可靠性,并能够执行更具挑战性的任务,但这些系统的工程设计非常复杂。这种复杂性不仅影响机器人团队的体系结构建模,还影响使团队能够完成其任务的协作智能的建模和分析。现有的多机器人应用开发方法并没有提供一个系统的机制来捕捉这些方面和评估多机器人系统的鲁棒性。我们通过引入ATLAS来解决这一差距,ATLAS是一种新颖的模型驱动方法,支持仿真中多机器人系统的系统鲁棒性分析。ATLAS领域特定语言可以对机器人团队及其任务的体系结构进行建模,并促进团队智能的规范。我们评估了ATLAS,并在使用MOOS-IvP机器人模拟器开发的无人水下航行器团队执行的两次海洋勘探任务中证明了它的有效性。
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