论文标题
对机器人技术和AI的行为树的调查
A Survey of Behavior Trees in Robotics and AI
论文作者
论文摘要
行为树（BTS）是作为启用计算机游戏模块化AI的工具发明的，但在过去的十年中，机器人社区中越来越关注。随着对代理AI复杂性的需求不断增长，游戏程序员发现，他们使用的有限状态机器（FSM）使用量表较差，并且难以扩展，适应和重复使用。在BTS中，状态过渡逻辑不是在各个状态中分散的，而是在分层的树结构中组织的，以叶子为叶子。这对模块化具有显着影响，进而简化了人类和算法的综合和分析。这些优点不仅在游戏AI设计中需要，而且还需要机器人技术，这是从研究中可以明显看出的。在本文中，我们介绍了对人工智能和机器人应用中BTS主题的全面调查。现有文献是根据方法，应用领域和贡献进行描述和分类的，并且本文以开放研究挑战的清单结束。
Behavior Trees (BTs) were invented as a tool to enable modular AI in computer games, but have received an increasing amount of attention in the robotics community in the last decade. With rising demands on agent AI complexity, game programmers found that the Finite State Machines (FSM) that they used scaled poorly and were difficult to extend, adapt and reuse. In BTs, the state transition logic is not dispersed across the individual states, but organized in a hierarchical tree structure, with the states as leaves. This has a significant effect on modularity, which in turn simplifies both synthesis and analysis by humans and algorithms alike. These advantages are needed not only in game AI design, but also in robotics, as is evident from the research being done. In this paper we present a comprehensive survey of the topic of BTs in Artificial Intelligence and Robotic applications. The existing literature is described and categorized based on methods, application areas and contributions, and the paper is concluded with a list of open research challenges.
