  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.
