Formal Modeling and Verification of Multi-Robot Interactive Scenarios in Service Settings

Livia Lestingi, Cristian Sbrolli, P. Scarmozzino, Giorgio Romeo, M. Bersani, Matteo G. Rossi
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引用次数: 4

Abstract

Service robots are increasingly widespread in healthcare and domestic assistance settings. Nevertheless, the literature still lacks robotic application development approaches that can deal with the complexity of multi-agent systems and the unpredictability of human behavior. We target this issue by building upon a model-driven development framework for human-robot interactive scenarios that relies on formal analysis (Statistical Model Checking) to estimate the probability of success of the robotic mission. We extend the framework’s scope to scenarios featuring multi-robot fleets, a broader range of human-robot interaction contingencies, and task handover between robots. We also present an extended model of human behavior to capture interaction patterns implying close contact or competition with the robot. In the latter case, the user can specify alternative mission plans for the robot, depending on the competition outcome. We illustrate the approach’s effectiveness and scalability through a case study from the healthcare setting, featuring multiple mobile robots and humans with diverse physiological characteristics and requesting a broad spectrum of services.
服务环境中多机器人交互场景的形式化建模与验证
服务机器人在医疗保健和家庭辅助环境中越来越普遍。然而,文献仍然缺乏能够处理多智能体系统复杂性和人类行为不可预测性的机器人应用程序开发方法。为了解决这个问题,我们建立了一个模型驱动的开发框架,用于人机交互场景,该框架依赖于形式分析(统计模型检查)来估计机器人任务成功的概率。我们将框架的范围扩展到具有多机器人车队,更广泛的人机交互突发事件以及机器人之间的任务移交的场景。我们还提出了一个扩展的人类行为模型,以捕捉暗示与机器人密切接触或竞争的交互模式。在后一种情况下,用户可以根据比赛结果为机器人指定备选任务计划。我们通过一个医疗环境的案例研究来说明该方法的有效性和可扩展性,该研究以具有不同生理特征的多个移动机器人和人类为特征,并要求提供广泛的服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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