Autonomous robots combine skills to form increasingly complex behaviors, called missions. While skills are often programmed at a relatively low abstraction level, their coordination is architecturally separated and often expressed in higher-level languages or frameworks. State machines have been the go-to language to model behavior for decades, but recently, behavior trees have gained attention among roboticists. Originally designed to model autonomous actors in computer games, behavior trees offer an extensible tree-based representation of missions and are claimed to support modular design and code reuse. Although several implementations of behavior trees are in use, little is known about their usage and scope in the real world. How do concepts offered by behavior trees relate to traditional languages, such as state machines? How are concepts in behavior trees and state machines used in actual applications? This paper is a study of the key language concepts in behavior trees as realized in domain-specific languages (DSLs), internal and external DSLs offered as libraries, and their use in open-source robotic applications supported by the Robot Operating System (ROS). We analyze behavior-tree DSLs and compare them to the standard language for behavior models in robotics: state machines. We identify DSLs for both behavior-modeling languages, and we analyze five in-depth. We mine open-source repositories for robotic applications that use the analyzed DSLs and analyze their usage. We identify similarities between behavior trees and state machines in terms of language design and the concepts offered to accommodate the needs of the robotics domain. We observed that the usage of behavior-tree DSLs in open-source projects is increasing rapidly. We observed similar usage patterns at model structure and at code reuse in the behavior-tree and state-machine models within the mined open-source projects. We contribute all extracted models as a dataset, hoping to inspire the community to use and further develop behavior trees, associated tools, and analysis techniques.

Abstract Mobile robots are becoming increasingly important in society. Fulfilling complex missions in different contexts and environments, robots are promising instruments to support our everyday live. As such, the task of defining the robot’s mission is moving from professional developers and roboticists to the end-users. However, with the current state-of-the-art, defining missions is non-trivial and typically requires dedicated programming skills. Since end-users usually lack such skills, many commercial robots are nowadays equipped with environments and domain-specific languages tailored for end-users. As such, the software support for defining missions is becoming an increasingly relevant criterion when buying or choosing robots. Improving these environments and languages for specifying missions toward simplicity and flexibility is crucial. To this end, we need to improve our empirical understanding of the current state-of-the-art of such languages and their environments. In this paper, we contribute in this direction. We present a survey of 30 mission specification environments for mobile robots that come with a visual and end-user-oriented language. We explore the design space of these languages and their environments, identify their concepts, and organize them as features in a feature model. We believe that our results are valuable to practitioners and researchers designing the next generation of mission specification languages in the vibrant domain of mobile robots.

Autonomous robots combine a variety of skills to form increasingly complex behaviors called missions. While the skills are often programmed at a relatively low level of abstraction, their coordination is architecturally separated and often expressed in higher-level languages or frameworks. Recently, the language of Behavior Trees gained attention among roboticists for this reason. Originally designed for computer games to model autonomous actors, Behavior Trees offer an extensible tree-based representation of missions. However, even though, several implementations of the language are in use, little is known about its usage and scope in the real world. How do behavior trees relate to traditional languages for describing behavior? How are behavior tree concepts used in applications? What are the benefits of using them?