Adaptation Needs in Robotic Systems: Assessing Behavior Trees and Their Enhancement

2026-09-04

AI Summary

本文探讨了行为树在满足现代机器人系统适应性需求方面的不足，并通过文献研究和实证分析，提出了增强型行为树方法来解决动态环境下的适应性问题。

Abstract

Robotic systems increasingly operate in dynamic, uncertain, and open-ended environments, where design-time assumptions may no longer hold, and adaptation becomes necessary to maintain effective and safe operation. Behavior Trees (BTs) are widely used in robotic control architectures due to their modularity, readability, and reactivity. This raises a central question: are BTs sufficient to meet the adaptation needs of modern robotic systems? This paper investigates this question through a literature-driven study complemented by empirical validation. First, we derive a classification of robotic adaptation needs from the literature, organizing them into six categories: Knowledge, Perception, Actuation, System, Mission, and Environment. Then, we analyze the capabilities and limitations of classical BTs with respect to these needs. Then, we characterize BT-based approaches for adaptation from the existing literature and organize them into four primary families, i.e., generation, extension, evolution, and refinement, including approaches that combine multiple families. Our analysis shows that the modularity, flexibility, and reactivity of classical BTs are insufficient for adaptation needs involving runtime restructuring, reasoning under uncertainty, mission reinterpretation, learning, or integration with external knowledge and planning mechanisms. Enhanced BT approaches address several of these limitations, but to different extents and often with limitations of their own. Our findings relate adaptation needs to both the capabilities and limitations of classical and enhanced BTs, providing guidance on when classical BTs are sufficient, when enhanced mechanisms are needed, and which challenges remain or emerge for adaptive robotic control architectures.

Problem

• Robotic Systems
• Adaptation Needs
• Behavior Trees
• Dynamic Environments
• Uncertainty

Innovation

• Behavior Trees
• Adaptation Needs
• Enhanced BT Approaches
• Runtime Restructuring
• Reasoning Under Uncertainty