  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.
