Evaluating behavior trees

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems Pub Date : 2024-05-14 DOI:10.1016/j.robot.2024.104714

Simona Gugliermo , David Cáceres Domínguez , Marco Iannotta , Todor Stoyanov , Erik Schaffernicht

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引用次数: 0

Abstract

Behavior trees (BTs) are increasingly popular in the robotics community. Yet in the growing body of published work on this topic, there is a lack of consensus on what to measure and how to quantify BTs when reporting results. This is not only due to the lack of standardized measures, but due to the sometimes ambiguous use of definitions to describe BT properties. This work provides a comprehensive overview of BT properties the community is interested in, how they relate to each other, the metrics currently used to measure BTs, and whether the metrics appropriately quantify those properties of interest. Finally, we provide the practitioner with a set of metrics to measure, as well as insights into the properties that can be derived from those metrics.

By providing this holistic view of properties and their corresponding evaluation metrics, we hope to improve clarity when using BTs in robotics. This more systematic approach will make reported results more consistent and comparable when evaluating BTs.

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评估行为树

行为树（BT）在机器人界越来越受欢迎。然而，在已发表的越来越多的相关研究成果中，对 BT 的测量内容和报告结果时如何量化 BT 还缺乏共识。这不仅是因为缺乏标准化的测量方法，还因为有时在描述 BT 特性时使用的定义含糊不清。这项工作全面概述了业界感兴趣的 BT 特性、它们之间的关系、目前用于衡量 BT 的指标，以及这些指标是否恰当地量化了这些感兴趣的特性。最后，我们为实践者提供了一套衡量标准，以及从这些标准中得出的属性的见解。通过提供这种对属性及其相应评估标准的整体看法，我们希望在机器人技术中使用 BT 时能更加清晰。我们希望通过提供这种整体观点及其相应的评估指标，提高机器人技术中使用 BT 时的清晰度。这种更加系统化的方法将使 BT 评估报告的结果更加一致，更具可比性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Robotics and Autonomous Systems 工程技术-机器人学

CiteScore

9.00

自引率

7.00%

发文量

164

审稿时长

4.5 months

期刊介绍： Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.