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Autonomous robots combine skills to form increasingly complex behaviors,called missions. While skills are often programmed at a relatively lowabstraction level, their coordination is architecturally separated and oftenexpressed in higher-level languages or frameworks. State machines have been thego-to language to model behavior for decades, but recently, behavior trees havegained attention among roboticists. Although several implementations ofbehavior trees are in use, little is known about their usage and scope in thereal world.How do concepts offered by behavior trees relate to traditionallanguages, such as state machines? How are concepts in behavior trees and statemachines used in actual applications? This paper is a study of the key languageconcepts in behavior trees as realized in domain-specific languages (DSLs),internal and external DSLs offered as libraries, and their use in open-sourcerobotic applications supported by the Robot Operating System (ROS). We analyzebehavior-tree DSLs and compare them to the standard language for behaviormodels in robotics:state machines. We identify DSLs for both behavior-modelinglanguages, and we analyze five in-depth.We mine open-source repositories forrobotic applications that use the analyzed DSLs and analyze their usage. Weidentify similarities between behavior trees and state machines in terms oflanguage design and the concepts offered to accommodate the needs of therobotics domain. We observed that the usage of behavior-tree DSLs inopen-source projects is increasing rapidly. We observed similar usage patternsat model structure and at code reuse in the behavior-tree and state-machinemodels within the mined open-source projects. We contribute all extractedmodels as a dataset, hoping to inspire the community to use and further developbehavior trees, associated tools, and analysis techniques.

Behavior Trees and State Machines in Robotics Applications