Helpfulness as a Key Metric of Human-Robot Collaboration
This addresses the need for a clear metric to assess robotic effectiveness in collaborative tasks, though it appears incremental as it builds on existing concepts of human-robot interaction.
The paper tackles the problem of quantitatively measuring the helpfulness of robotic partners in human-robot collaboration by proposing a task-oriented metric applicable to various planning and execution paradigms, with preliminary results presented.
As robotic teammates become more common in society, people will assess the robots' roles in their interactions along many dimensions. One such dimension is effectiveness: people will ask whether their robotic partners are trustworthy and effective collaborators. This begs a crucial question: how can we quantitatively measure the helpfulness of a robotic partner for a given task at hand? This paper seeks to answer this question with regards to the interactive robot's decision making. We describe a clear, concise, and task-oriented metric applicable to many different planning and execution paradigms. The proposed helpfulness metric is fundamental to assessing the benefit that a partner has on a team for a given task. In this paper, we define helpfulness, illustrate it on concrete examples from a variety of domains, discuss its properties and ramifications for planning interactions with humans, and present preliminary results.