  Behavior Trees, which originated in video games as a method for controlling
NPCs but have since gained traction within the robotics community, are a
framework for describing the execution of a task. BehaVerify is a tool that
creates a nuXmv model from a py_tree. For composite nodes, which are
standardized, this process is automatic and requires no additional user input.
A wide variety of leaf nodes are automatically supported and require no
additional user input, but customized leaf nodes will require additional user
input to be correctly modeled. BehaVerify can provide a template to make this
easier. BehaVerify is able to create a nuXmv model with over 100 nodes and
nuXmv was able to verify various non-trivial LTL properties on this model, both
directly and via counterexample. The model in question features parallel nodes,
selector, and sequence nodes. A comparison with models based on BTCompiler
indicates that the models created by BehaVerify perform better.
