Behavior Trees in Action: A Study of Robotics Applications
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Abstract (arXiv)
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? We present a study of the key language concepts in Behavior Trees and their use in real-world robotic applications. We identify behavior tree languages and compare their semantics to the most well-known behavior modeling languages: state and activity diagrams. We mine open source repositories for robotics applications that use the language and analyze this usage. We find that Behavior Trees are a pragmatic language, not fully specified, allowing projects to extend it even for just one model. Behavior trees clearly resemble the models-at-runtime paradigm. We contribute a dataset of real-world behavior models, hoping to inspire the community to use and further develop this language, associated tools, and analysis techniques.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Oct 2020.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 4; 2026: 1.
8 papers.
- 2023Robot Behavior-Tree-Based Task Generation with Large Language Modelscited by 22
- 2025ManipDreamer: Boosting Robotic Manipulation World Model with Action Tree and Visual Guidancecited by 11
- 2022KT-BT: A Framework for Knowledge Transfer Through Behavior Trees in Multi-Robot Systemscited by 6
- 2025MinionsLLM: a Task-adaptive Framework For The Training and Control of Multi-Agent Systems Through Natural Languagecited by 1
- 2025LLM-Driven Self-Refinement for Embodied Drone Task Planningcited by 1
- 2024Execution Semantics of Behavior Trees in Robotic Applicationscited by 0
- 2025CARJAN: Agent-Based Generation and Simulation of Traffic Scenarios with AJANcited by 0
- 2026A Glimpse into Long-term Physical Coexistence with Intelligent Robotscited by 0
- 2026A Glimpse into Long-term Physical Coexistence with Intelligent Robots13 Jul 2026
- 2025CARJAN: Agent-Based Generation and Simulation of Traffic Scenarios with AJAN29 Aug 2025
- 2025LLM-Driven Self-Refinement for Embodied Drone Task Planning21 Aug 2025
- 2025MinionsLLM: a Task-adaptive Framework For The Training and Control of Multi-Agent Systems Through Natural Language1 Aug 2025
- 2025ManipDreamer: Boosting Robotic Manipulation World Model with Action Tree and Visual Guidance23 Apr 2025
- 2024Execution Semantics of Behavior Trees in Robotic Applications31 Jul 2024
- 2023Robot Behavior-Tree-Based Task Generation with Large Language Models24 Feb 2023
- 2022KT-BT: A Framework for Knowledge Transfer Through Behavior Trees in Multi-Robot Systems7 Sep 2022