2022/08/10 by Serbinowska, Serena S., Taylor T. Johnson, Johnson, Taylor T.
Computer Science · #Artificial Intelligence in Games #FOS: Computer and information sciences #Formal Methods in Verification #Reinforcement Learning in Robotics #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2208.05360
openalex publication_date 2022/08/10 · openalex created_date 2022/08/12 · openalex updated_date 2026/07/28
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 pytree. 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.