Behavior Trees for Robotic Systems: An Empirical Study on Practices and Experiences

2026-09-18

AI Summary

研究通过实证方法探讨行为树在机器人系统中的应用，结合技术行动研究和问卷调查，解决实际采用中的设计、集成及工具支持等问题。

Abstract

Over the last decade, behavior trees (BT) have become one of the dominant behavior models for coordinating missions of robotic systems. Yet empirical evidence on BT adoption in real-world contexts remains limited, especially regarding practitioners experiences and practices. Without practitioner-grounded evidence from both academic and industrial settings, the research community risks developing guidelines and tools that are plausible in principle but only partly aligned with real challenges. This scarcity of evidence leads to ad-hoc practices, impeding software reuse, maintenance, and evolution. This paper reports a mixed-methods study combining a technical action research investigation at an automotive company with a survey of 34 robotics practitioners. Our results indicate that BTs improve team communication and the understandability of robotic decision-making logic, reflecting BTs practical value beyond mission coordination. At the same time, practitioners face multiple non-trivial design and integration decisions, complicated by the lack of adequate guidelines and tool support. These decisions span architectural and language choices when implementing BTs and integrating them within ROS, for which we report observed patterns. Additionally, practitioners faced multi-factor granularity decisions and mixed experiences with current libraries. For the most used BT libraries, they reported implementation challenges and documentation gaps. Regarding planning algorithms, practitioners find deciding optimal BT node ordering challenging. Views on scalability remained inconclusive, and limitations in current libraries and practices hinder broader adoption. We conclude with cross-cutting observations and implications for both practitioners adopting BTs in robotic systems and researchers aiming to advance empirical understanding of BT adoption.

Problem

• Behavior Trees
• Empirical Study
• Practitioners' Experiences
• Real-World Contexts
• Software Reuse

Innovation

• Behavior Trees
• Robotics
• Practitioner Experience
• Integration Challenges
• ROS