This article investigates the analysis of robotic system models using the Robotic System Hierarchic Petri Net (RSHPN) meta-model, proposing streamlined methods by focusing on significant system fragments and inheriting properties from the meta-model. Our research demonstrates that it is feasible to: 1) effectively analyze complex robotic systems expressed using RSHPN, and 2) enable models to inherit properties from the meta-model. This approach significantly simplifies the analysis process, reduces design time, and ensures the safety and reliability of the systems. These aspects are crucial for robots operating in human environments. Our results suggest that Petri nets could be further explored as a useful tool for the formal description and in-depth analysis of the properties of robotic systems.

翻译：本文研究了利用机器人系统层次Petri网（RSHPN）元模型对机器人系统模型进行分析的方法，通过聚焦于关键系统片段并继承元模型的属性，提出了简化的分析流程。我们的研究表明：1）能够有效分析使用RSHPN表达的复杂机器人系统；2）使模型能够继承元模型的属性。该方法显著简化了分析过程，缩短了设计时间，并确保了系统的安全性与可靠性。这些特性对于在人类环境中运行的机器人至关重要。我们的结果表明，Petri网可进一步发展为机器人系统形式化描述及属性深度分析的有效工具。