基于响应机器人标准测试方法实现人机交互评价

Adam Norton, Brian Flynn, H. Yanco
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引用次数: 4

摘要

ASTM E54.09国土安全应用委员会制定的标准测试方法;响应机器人已经为机器人社区服务了超过15年。通过该委员会指定的测试方法提供了一个通用的框架、可扩展的结构和可扩展的测试设备,可用于锻炼许多不同的机器人能力。近年来,该委员会强调了如何将测试方法用于培训目的,以评估操作员的熟练程度。机器人系统的人机交互(HRI)特性,包括它的控制界面,对操作员的表现有特别大的影响。操作员对机器人系统的了解以及如何有效地使用它也会影响性能。为此,提出了两项可能的标准工作,有助于描述和证明有效的人力资源评价。首先是扩展现有的记录机器人配置的标准实践,以包括HRI特征和测量这些特征有效性的方法。第二个是一个新的标准实践,旨在通过引入可变测试设备设置来引出操作人员和系统的决策能力,从而展示有效的HRI。该实践的目标是向标准社区强调HRI技术,例如利用辅助自主功能来避免障碍和减少错误。通过以这些方式纳入HRI评估,HRI可以被视为响应机器人系统的一个组成部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementing Human-Robot Interaction Evaluation Using Standard Test Methods for Response Robots
Adam Norton1, Brian Flynn1, and Holly Yanco1 ABSTRACT The standard test methods developed through the ASTM E54.09 Committee on Homeland Security Applications; Response Robots have served the robotics community for over a decade and a half. The test methods specified through this committee provide a common framework, scalable structure, and malleable test apparatuses that can be used to exercise many different robotic capabilities. In recent years, the committee has emphasized how the test methods can be used for training purposes to evaluate operator proficiency. The human-robot interaction (HRI) characteristics of a robot system, including its control interface, are particularly influential to operator performance. The operator’s knowledge of the robot system and how to use it effectively will also affect performance. To this end, two potential standards efforts are proposed that can aid in characterizing and demonstrating effective HRI. The first is an expansion of an existing standard practice for recording robot configuration to include HRI characteristics and methods by which to measure the effectiveness of these characteristics. The second is a new standard practice that is aimed at demonstrating effective HRI by introducing variable test apparatus settings to elicit decision-making capabilities from the operator and system. The goal of this practice is to highlight HRI techniques to the standards community, such as utilizing assistive autonomous functionality for obstacle avoidance and error mitigation. By incorporating HRI evaluation in these ways, HRI can be seen as an integral component of a response robot system.
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