The need for high-level autonomy and robustness of autonomous systems for missions in dynamic and remote environment has pushed developers to come up with new software architectures. A common architecture style is to summarize the capabilities of the robotic system into elementary actions, called skills, on top of which a skill management layer is implemented to structure, test and control the functional layer. However, current available verification tools only provide either mission-specific verification or verification on a model that does not replicate the actual execution of the system, which makes it difficult to ensure its robustness to unexpected events. To that end, a tool, SkiNet, has been developed to transform the skill-based architecture of a system into a Petri net modeling the state-machine behaviors of the skills and the resources they handle. The Petri net allows the use of model-checking, such as Linear Temporal Logic (LTL) or Computational Tree Logic (CTL), for the user to analyze and verify the model of the system.
翻译:在动态和偏远环境中,特派团需要高度自主和自主系统的稳健性,这促使开发者提出新的软件结构。一个共同的结构风格是将机器人系统的能力总结为基本行动,称为技能,并首先实施技能管理层,以构建、测试和控制功能层。然而,目前可用的核查工具只提供特派团特有核查或核查,不重复系统实际运行的模型,因此难以确保系统对意外事件的稳健性。为此,开发了一个工具SkiNet,将系统基于技能的架构转换成一个Petrii网,以模拟其所处理的技能和资源的状态机器行为模式。Petri网络允许使用模型检查,如线性温度逻辑(LTL)或对立树逻辑(CTL)等模型,供用户分析和核实系统模型。