Behavior trees (BTs) are increasingly popular in the robotics community. Yet in the growing body of published work on this topic, there is a lack of consensus on what to measure and how to quantify BTs when reporting results. This is not only due to the lack of standardized measures, but due to the sometimes ambiguous use of definitions to describe BT properties. This work provides a comprehensive overview of BT properties the community is interested in, how they relate to each other, the metrics currently used to measure BTs, and whether the metrics appropriately quantify those properties of interest. Finally, we provide the practitioner with a set of metrics to measure, as well as insights into the properties that can be derived from those metrics. By providing this holistic view of properties and their corresponding evaluation metrics, we hope to improve clarity when using BTs in robotics. This more systematic approach will make reported results more consistent and comparable when evaluating BTs.
This work was partially supported by the Swedish Foundation for Strategic Research (SSF) (project ID19-0053), the Industrial Graduate School Collaborative AI & Robotics (CoAIRob), funded by the Swedish Knowledge Foundation under Grant Dnr:20190128, and by the European Union’s Horizon Europe Framework Programme under grant agreement No 101070596 (euROBIN).