Helpfulness as a Key Metric of Human-Robot Collaboration

TL;DR

This paper introduces a quantitative, task-oriented helpfulness metric to evaluate the effectiveness of robotic partners in human-robot collaboration, applicable across various planning paradigms.

Contribution

It proposes a novel, clear helpfulness metric for assessing robotic assistance, with examples, properties, and preliminary validation across different domains.

Findings

The helpfulness metric effectively measures robot contribution in collaborative tasks.

Preliminary results demonstrate the metric's applicability across multiple domains.

The metric informs better planning and interaction strategies for human-robot teams.

Abstract

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.